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Data Analyst, Clinical Data Effectiveness

Clover Health

Location: USA Advertised pay: USD 77,000–100,000 / yearly Work arrangement: Region-restricted remote Employment: Full Time Posted: October 24, 2026 Freshness: Posted today Source check: Observed very recently

Executive opportunity brief

The decision in one screen

A compact evidence-first read of compensation, flexibility, mobility and what still needs verification. No universal quality score is used.

Compensation positionBelow the current lower quartile77 current same-currency observations
Work flexibilityRegion-restricted remoteBased only on stated location/work-arrangement evidence.
Decision evidence4 of 5 core facts knownThis listing states more core decision facts than the median role in the current sample.
Mobility evidenceSponsorship not establishedUnknown evidence is not treated as unavailable.
Current alternativesCurrent role context limitedCurrent HPJ inventory, not the whole labor market.
Negotiation readinessNegotiation evidence available: advertised pay range, current same-currency market context, strong decision evidence.Use the private Offer & Negotiation Lab below if an offer arrives.
Watch closely: Application closing time

Fast read

Opportunity DNA

This opportunity needs a closer read before drawing a strong conclusion, especially around location rules could change the fit.

PayRange available

Current comparable position is around the 4th percentile.

FlexibilityLocation limits visible

Geographic eligibility is restricted to a country or region.

Entry pathRequirements unclear

The listing does not make the minimum education or experience threshold clear enough yet.

MobilityNot established

Sponsorship and relocation support are not clear from the current listing.

ApplicationSome process detail

Part of the application route can be assessed, but the full external process may contain additional steps.

TraceabilityCurrent source traceable

At least one recent enabled source can still renew this vacancy.

This fingerprint summarizes what is clear, constrained or still unanswered in the current listing. It is a reading aid, not an overall job score.

Decision evidence check

4 of 5 core facts stated

This checks whether the listing states the facts that commonly change an employment decision. It measures disclosure completeness, not whether the opportunity is good or bad.

Facts already stated

  • Compensation
  • Work arrangement
  • Location eligibility
  • Employment type

What to verify next

  • Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?

Unknown information is never converted into a negative score. The questions above exist to prevent missing evidence from being mistaken for a favorable term.

Decision levers

What could make or break the fit?

Reasons to look closer

Nothing stands out strongly enough yet to call a clear advantage. The role may still be attractive for reasons the listing does not spell out.

Trade-offs to weigh

  • Location rules could change the fit: Geographic eligibility is restricted to a country or region.

Questions worth asking before you invest more time

  • Confirm whether a degree is actually required, preferred, or replaceable with equivalent experience.
  • Confirm the actual minimum experience requirement rather than assuming preferred background is mandatory.
  • Ask whether visa sponsorship is available before investing significant time in the application.

These questions come from details the listing leaves open. An unanswered point is not treated as a disadvantage.

Opportunity neighborhood

Keep your options open

These live roles sit close enough to this opportunity to make useful comparison points. Look across several employers before deciding what pay, flexibility or access trade-offs you are willing to accept.

Lead Machine Learning Engineer

Serve Robotics · Canada, USA

USD 225,000–260,000 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same country · Similar work arrangement · Same employment type

About 174% higher advertised midpoint

Senior Machine Learning Engineer, Ads - Quora

Quora · Canada, Ireland, USA

USD 189,507–274,604 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same country · Similar work arrangement · Same employment type

About 162% higher advertised midpoint

Senior Data Analyst, GTM Analytics - US

Luxury Presence · USA

USD 145,000–175,000 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same country · Similar work arrangement · Same employment type

About 81% higher advertised midpoint

Associate Data Engineer

BeyondTrust · Anywhere in the World

Salary not disclosed Worldwide remote 4/5 core facts

Why it is nearby: Similar work arrangement · Same employment type · Recently posted

Different angle: Seniority is not explicit

This neighborhood is drawn from current inventory in the same broad occupation. Similarity is based on explicit listing facts; missing details do not count against a job.

Role market context

How much current choice is visible around this kind of work?

This compares the vacancy with current High Paid Job inventory in the broad Data & AI roles family. It describes visible choice and disclosure, not future demand or career quality.

Current visible roles987

200 most recent current roles sampled for the disclosure measures below.

Employers represented137

Distinct employers in the bounded current sample, not an estimate of all employers hiring in the market.

Decision-ready disclosure28%

Current sampled roles stating at least four of the five Core Decision Facts.

Compensation stated19%

Requires a numeric amount, explicit ISO currency and supported pay period.

Work arrangement stated98%

Listings with explicit enough remote, hybrid or on-site evidence to classify.

Stated closing time18%

Missing deadline evidence remains unknown and is not interpreted as an open-ended application window.

Disclosure comparison: This listing states more core decision facts than the median role in the current sample. This listing: 4/5 · sample median: 3.0/5.

Currencies with explicit pay evidence in the sample: USD (26) · GBP (5) · EUR (4) · CAD (3). Raw amounts across different currencies are not compared.

This describes current visible High Paid Job inventory in the same broad occupation family. Percentages use a bounded recent sample and are not a forecast, a complete labor-market census or an employer-quality measure.

Constraint opportunity lab

What changes the size of the current opportunity pool?

Each line applies one stricter evidence-based constraint to the same bounded current role-family sample. It helps you see the trade-off in visible choice without deciding which trade-off is right for you.

Require explicit sponsorship or relocation support 5 / 200 3%

Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.

Require worldwide remote evidence 22 / 200 11%

A much stricter subset: only listings with explicit worldwide-remote evidence remain.

Require usable compensation disclosure 38 / 200 19%

Requires amount, explicit ISO currency and a supported pay period. Missing pay evidence remains unknown.

Require at least four Core Decision Facts 56 / 200 28%

Shows the subset with enough stated evidence for a more informed first comparison.

Stay in the same stated country 23 / 75 31%

Uses only roles where a country is known. Roles without country evidence are excluded from this denominator.

Require a remote-listed arrangement 63 / 200 32%

Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.

Keep the same employment type 117 / 128 91%

Uses only roles with a stated employment type.

Keep this advertised salary floor in the same currency 24 / 26 92%

Only same-currency opportunities with usable annualized pay enter this comparison. Other currencies are not converted or treated as lower.

These are counterfactual filters over a bounded sample of current HPJ inventory in the same broad occupation family. They show how visible choice changes when one evidence-based constraint is applied; they do not tell you which constraint you should choose or predict hiring outcomes. The calculation uses the 200 most recent current roles from 987 visible roles in this broad family.

Salary transparency context

Is pay disclosure typical for this kind of role?

This listing states usable structured compensation. About 19% of the bounded current role sample does the same.

This listingUsable pay stated

Compensation counts only when amount, ISO currency and supported pay period are all known.

Current same-role sample19%

Pay disclosure is uncommon in the current role sample.

Current employer pattern55%

This employer’s current visible listings disclose pay materially more often than the current same-role sample.

This compares salary-disclosure behavior in current visible listings. It does not compare raw salary amounts across currencies, infer undisclosed pay as zero, or rate employer quality.

Private offer & negotiation lab

Turn an offer into evidence, not guesswork

Enter an annual base offer and, if you want, your own target. HPJ compares only within one explicit currency and never chooses a target for you.

Advertised annualized payUSD 77,000–100,000 / yearListing evidence only.
Current comparable medianUSD 170,25226 current sampled roles
Current upper quartileUSD 194,875Current HPJ inventory context, not a salary recommendation.

Negotiation evidence available: advertised pay range, current same-currency market context, strong decision evidence.

Enter an annual base offer to compare it with explicit same-currency evidence. HPJ will not suggest a target for you.

Review the full package · 10 terms

Mark what is confirmed, what needs clarification and what you want to prioritize. These choices and notes stay in this browser.

Base payKnown

Usable advertised compensation is available.

Bonus / commissionMentioned

Variable compensation is mentioned; verify amount, formula, target and eligibility.

Equity / long-term incentivesMentioned

Equity or long-term incentive language is mentioned; verify grant type, vesting and valuation basis.

Retirement / pensionMentioned

Retirement or pension benefits are mentioned; verify employer contribution and vesting.

Health benefitsMentioned

Health-benefit language is mentioned; verify coverage, dependants and employee cost.

Paid leaveVerify

Paid-leave language is mentioned; verify the exact entitlement and carry-over rules.

Work arrangementKnown

A work-arrangement signal is available; verify schedule details before relying on it.

RelocationVerify

Relocation support not established

Visa / work authorizationVerify

Sponsorship not established

Review timingVerify

A review cycle is mentioned; verify timing and whether compensation can change at that review.

Questions worth taking into the offer conversation

  • How much paid leave is provided and what are the carry-over or blackout rules?
  • If relocation is relevant, what expenses, timing and repayment conditions are covered?
  • What exact sponsorship or work-authorization conditions apply to this role?
  • When is the first performance and compensation review after joining?
  • Is there a firm application deadline, a rolling review window or no stated closing date?

Occupation intelligence

What broader career references connect to this role?

HPJ uses broad comparison families for current-market analysis. External taxonomy results are reference candidates for that broad family, not a declaration that this vacancy has been authoritatively classified into a specific occupation.

HPJ comparison familyData & AI roles
Adjacent families worth exploringSoftware engineering roles · Product roles

European occupation references

This service uses the ESCO classification of the European Commission.

U.S. occupation references

This site incorporates information from O*NET Web Services by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). O*NET® is a trademark of USDOL/ETA.

Career reference research

Skills worth investigating

Official occupational context, paired with exact phrases visible in this vacancy. It is not a skills test or an applicant-fit score.

ESCO · European occupation

data scientist

Usually essential in this ESCO occupation
  • statistical modeling techniques
  • perform project management
  • query languages
  • online analytical processing
  • develop data processing applications
  • data engineering
  • manage data collection systems
Context-dependent ESCO skills
  • manage ICT data architecture
  • SPARQL
  • use spreadsheets software
  • computational biology
  • state estimation

O*NET · U.S. occupation

Data Scientists

O*NET occupation skills
  • Mathematics
  • Critical Thinking
  • Reading Comprehension
  • Complex Problem Solving
  • Programming
  • Active Learning
  • Speaking
  • Active Listening
Build my private skill preparation brief Your evidence · Practice · Interview questions

Plan how you might demonstrate or investigate occupational skills. These are broad-family reference examples, not confirmed vacancy requirements. Nothing you enter is sent to High Paid Job.

statistical modeling techniquesESCO · Essential · Listing mention unknown
perform project managementESCO · Essential · Listing mention unknown
query languagesESCO · Essential · Listing mention unknown
online analytical processingESCO · Essential · Listing mention unknown
develop data processing applicationsESCO · Essential · Listing mention unknown
data engineeringESCO · Essential · Listing mention unknown
manage data collection systemsESCO · Essential · Listing mention unknown
manage ICT data architectureESCO · Optional · Listing mention unknown
SPARQLESCO · Optional · Listing mention unknown
use spreadsheets softwareESCO · Optional · Listing mention unknown
computational biologyESCO · Optional · Listing mention unknown
state estimationESCO · Optional · Listing mention unknown
MathematicsO*NET · Skills · Listing mention unknown
Critical ThinkingO*NET · Skills · Listing mention unknown
Reading ComprehensionO*NET · Skills · Listing mention unknown
Complex Problem SolvingO*NET · Skills · Listing mention unknown
ProgrammingO*NET · Skills · Listing mention unknown
Active LearningO*NET · Skills · Listing mention unknown
SpeakingO*NET · Skills · Listing mention unknown
Active ListeningO*NET · Skills · Listing mention unknown

Private to this browser. Up to 20 reference skills; not a qualification assessment or hiring prediction.

Useful next question: Which of these occupational reference skills does the hiring manager actually expect for this specific role, and what evidence would demonstrate them?

These skills belong to one reference occupation selected for HPJ’s broad career family, not a verified classification of this vacancy. Text overlap only means a phrase appears in the available listing text; it does not establish an employer requirement, your proficiency, or a qualification gap. A missing mention is unknown, not a deficit.

Adjacent current roles to investigate

Adjacent-family roles are exploration prompts from current HPJ inventory. They are not inferred qualification matches and they do not imply a promotion path.

Skill bridge

What does this role connect to?

Python is one of the signals this listing shares with skills appearing often across current Data & AI roles opportunities.

Skills named in this listing

PythonSQL

Shared with the current career sample

  • Python Seen in 90 sampled listings
  • SQL Seen in 81 sampled listings

Combinations also appearing together

  • Python + SQL appeared together in 65 sampled listings

Application edge

  • If these skills match your background, prepare one concrete example that shows how you used Python and SQL rather than relying on a keyword-only claim.

If the named skills are genuinely transferable in your own experience, the occupation map also points to adjacent current families worth researching: Software engineering roles and Product roles. This is exploration context, not a qualification match.

Skill signals come from explicit text mentions. A mention is not automatically a requirement, and absence from the current top-skill list does not make a skill rare or unimportant. The current career comparison draws on 120 sampled listings; 115 contain a recognized skill signal.

Application Decision Lab

Turn the listing into a preparation plan

Separate what the listing actually states from what you still need to prepare or verify. Your selections and short notes stay in this browser and are never submitted to High Paid Job.

Listing mention

Python

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

SQL

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Questions worth resolving before you rely on the opportunity

  • Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
  • Work authorization / sponsorship: If sponsorship or work authorization matters to you, what exact immigration or employer-sponsorship conditions apply to this role?
  • Application process: What interview, assessment, portfolio, reference or screening stages are part of the hiring process?

Decision analysis

What the listing really tells you

Useful decision context

The headline alone does not tell the whole story for Data Analyst, Clinical Data Effectiveness at Clover Health. The clearest decision context comes from pay has a useful comparison point, remote flexibility can be weighed properly, and the application route gives a few useful clues.

Pay has a useful comparison point

Among 77 current comparable salaries in USD, the normalized annual midpoint is around the 4th percentile. This compares advertised pay in the same currency and does not include every element of total compensation.

Remote flexibility can be weighed properly

Location flexibility can be assessed here: Remote with some uncertainty or restrictions, with a Remote Freedom reading of 62/100. One practical limit to notice is geographic eligibility is restricted to a country or region..

The application route gives a few useful clues

Provider-mediated application path. The external application may contain additional steps that are not visible from the listing itself.

Source continuity adds useful context

1 recent enabled source can currently renew this vacancy across 1 source classes. That improves traceability, although it does not verify the employer itself.

How this analysis is assembled

This read combines the structured details currently available for pay, flexibility, qualifications, mobility, application effort and source continuity. Missing facts are left open for you to verify.

Analysis evidence coverage

How much analysis can the current evidence support?

100%Strong analysis evidence coverage
100%
Current-sample pay position4 / 100

Uses the explainable High Pay Score within the job’s current occupation/seniority/currency comparison sample.

Remote Freedom evidence62 / 100

Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.

Salary evidence qualityHigh confidence · Focused salary range

The configured source supplied structured salary fields, a usable currency and a focused comparison value.

Listing freshnessPosted today

The source posting date is today.

Source provenance evidenceEstablished source evidence

At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.

There is no universal opportunity score because pay, flexibility and access matter differently to different people. Compare Jobs lets you weight the evidence around your own priorities.

Decision checklist

What is supported, uncertain or worth checking?

This checklist separates supported strengths, visible cautions and missing evidence. It is not an overall recommendation or guarantee that the job is suitable for you.

Supported strengths

No standout strength is supported strongly enough to list here. That is not a negative rating.

Visible cautions

  • Geographic eligibility is restricted to a country or region.
  • Some compensation may be variable or performance-based. Confirm the guaranteed base amount before comparing headline pay.
  • This is remote work with a geographic restriction, not a worldwide-remote vacancy.

Still unknown

  • Visa sponsorship is not established by the available listing data.

Qualifications & access

What qualifications are explicitly stated?

Entry-barrier evidence limited

EducationEducation requirement not established
Required experience evidenceExperience requirement not established
Explicit required barriers0
Explicit access signals0

Qualification signals come from explicit listing wording. Anything not mentioned remains unknown, so silence is never treated as proof that a degree, experience, licence or other requirement is unnecessary.

Pay vs. barriers

Pay and barrier context available

The current pay position can be viewed alongside the stated barriers, but the available detail does not support a stronger conclusion.

Current-sample pay position

Comparable disclosed-pay evidence places this job at about 4 / 100 within its current occupation/seniority sample.

Location-freedom constraints

1 explicit Remote Freedom restriction signal is present and is shown separately from qualification requirements.

Evidence gaps that could change this interpretation
  • Education requirement is not established.
  • Required prior-experience level is not established.

This section weighs pay context against clearly stated barriers without collapsing unlike requirements into one universal score. Degree, experience, licensing, clearance and location limits remain separate, and missing qualification details stay unknown.

Beyond the headline

Not enough evidence for a hidden-value finding

Potential hidden value appears only when several distinct non-pay advantages are actually supported. Missing requirements or benefits are never counted as positives.

Still check: The current application path is provider-mediated rather than directly classified as an employer-authorized or official route.

Hidden Value is an experimental evidence summary, not an investment-style score or guarantee of employability. It only uses explicit current listing evidence and does not infer that an unmentioned qualification is unnecessary.

Explainable opportunity highlight

Why this opportunity stands out

These are supported signals from the current listing and comparison sample—not a guarantee that this is the best job for you.

Clear compensation evidence

The source provides structured salary information with a comparatively focused range, improving the usefulness of pay comparisons.

Fresh opportunity

The source posting date is today.

Compensation intelligence

How competitive is this pay?

4/100

Below many comparable disclosed salaries

4%
Comparison familyData & AI roles
Comparable salaries77
Current-sample medianUSD 175,000
Middle 50% of sampleUSD 132,500–209,000
Position in sampleAt or above about 4%
Comparison geographySame country (US)
Pay positionBelow the current lower quartile

The annualized midpoint is below the 25th percentile boundary of the current comparable sample.

Why this analysis?

  • This score reflects the current advertised-pay distribution for comparable active jobs in the same currency. It measures pay position, not overall job quality.
  • Salary confidence: High. The configured source supplied structured salary fields, a usable currency and a focused comparison value.
  • Range quality: Focused salary range.

Employer compensation communication

Pay transparency at Clover Health

Mixed current pay transparency

This score uses the employer’s current visible listings and combines how often pay is disclosed with how useful those ranges are. Bonus, equity and benefit mentions are shown separately and do not raise the score.

63/100
63%
Salary disclosure55% · 11 of 20 sampled listings
Range qualityMostly focused or specific pay information
Bonus wording13 current listings
Equity wording13 current listings
Benefits wording13 current listings
Evidence strengthStronger

This pattern comes from the employer’s current visible vacancies. It describes hiring and pay transparency in those listings, not employee satisfaction or a permanent judgement of the employer.

Current employer intelligence

Clover Health — current opportunity snapshot

Current opportunities visible20
Salary disclosure55%
Remote-policy evidence coverage100% · 20 of 20 sampled listings
Remote share of known arrangements100%
Worldwide-remote share45%
Known hiring countries1
Sponsorship evidence coverage0% · 0 of 20 sampled listings
Explicit sponsorship outcomes0 confirmed · 0 possible · 0 unavailable
Pattern sample20 of 20 · 100% coverage
Current role-family breadth5
Stated closing-date coverage45%
Relocation evidence coverage0% · 0 explicitly offered
Posted within 7 days30% of listings with a known posting date

Employer Evidence Profile

How often this employer’s current visible sampled vacancies state decision-critical information. These percentages describe evidence coverage, not employer quality.

Compensation55% of sampled current listings

Current sampled listings with advertised compensation evidence.

Work arrangement100% of sampled current listings

Current sampled listings whose work arrangement is clearer than unknown.

Location60% of sampled current listings

Current sampled listings with a supported country signal.

Application timing45% of sampled current listings

Current sampled listings with an explicit closing time.

Posting date100% of sampled current listings

Current sampled listings with a usable posting date.

Sponsorship0% of sampled current listings

Current sampled listings that explicitly indicate confirmed, possible or unavailable sponsorship evidence.

Relocation0% of sampled current listings

Current sampled listings with an explicit relocation signal.

Low coverage means the current visible listings state the information less often. It does not prove that the employer lacks the policy, benefit or support.

Common current occupation families: Executive (6) · Data & AI (3) · Operations (2)

Visible seniority mix: Senior / lead (8) · Leadership (8)

Current employment-type mix: Full time (20)

Most visible hiring countries in this sample: United States (12)

Other current roles from this employer

These are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.

Current disclosed salary medians by currency

  • USD 175,000 median · 11 disclosed salaries

Questions worth asking this employer

  • What compensation range applies to this role, and which parts of total compensation are fixed versus variable?
  • If work authorization matters to you, what sponsorship policy applies to this specific role and location?
  • If a move is required, is relocation assistance available for this position?
  • What is the expected application and interview timeline if the listing does not state a closing date?

These questions are prompted by missing or thin evidence in the employer’s current visible vacancies. Missing evidence is not treated as a negative judgement.

This employer snapshot uses the employer’s current visible listings. Remote and sponsorship rates use only vacancies with explicit evidence, while missing information stays unknown. Salary medians are shown separately by currency and need at least five disclosed salaries. Zero confirmed sponsorship means none was explicitly found in this sample, not that sponsorship is unavailable.

This snapshot describes the employer’s current visible vacancies—things such as pay disclosure and work arrangement. It is not an employee-satisfaction or hiring-quality rating, and different currencies stay separate.

Work-location intelligence

Remote Freedom

62/100

Remote with some uncertainty or restrictions

62%

Why this score?

  • The role is remote but the source identifies a country or regional restriction.

Location restrictions detected

  • Geographic eligibility is restricted to a country or region.

Remote Freedom measures observable location flexibility only. Unknown work-location information remains unscored. Timezone wording is penalized only when it appears restrictive; general collaboration across time zones is not treated as a restriction. A score does not guarantee legal work eligibility, payroll availability or visa sponsorship.

International applicant intelligence

Visa & relocation signals

Sponsorship status is shown only when the listing provides clear enough wording. Employer history or headquarters location is not used to guess an answer.

Visa sponsorshipSponsorship not established

The available listing details do not contain a clear enough sponsorship statement.

RelocationRelocation support not established

The available listing details do not contain a clear enough relocation statement.

Tradeoff check

What’s the catch?

These are visible conditions worth checking before treating the headline compensation as the whole story:

  • Some compensation may be variable or performance-based. Confirm the guaranteed base amount before comparing headline pay.
  • This is remote work with a geographic restriction, not a worldwide-remote vacancy.

Current alternatives

Better-paying alternatives

These current roles show a materially higher annualized salary midpoint in the same broad occupation and currency. Similar seniority, country, work arrangement, employment type and recency are preferred where possible; higher pay alone does not make an alternative a better fit.

About +163% midpoint

Applied AI Engineer

Future PLC · USA

USD 215,000–250,000 / year Region-restricted remote

Why comparable: Same country · Similar work-location arrangement · Same employment type

Check: Seniority is not explicit in the alternative listing.

About +123% midpoint

Analytics Engineer

Reddit · USA

USD 164,200–229,990 / year Region-restricted remote

Why comparable: Same country · Similar work-location arrangement · Same employment type

Check: Seniority is not explicit in the alternative listing.

About +98% midpoint

Data Engineer (FedD024)

Defense Unicorns · USA

USD 148,750–201,250 / year Region-restricted remote

Why comparable: Same country · Similar work-location arrangement · Same employment type

Check: Seniority is not explicit in the alternative listing.

Alternatives are drawn from the current inventory rather than presented as application recommendations. A pay difference needs to be meaningful—about 3% or more at the midpoint—and different currencies are not compared.

Application-path intelligence

What can we see about the application process?

Provider-mediated application path

The current application path comes through a publisher or aggregator. The destination may still lead to an employer-authorized hiring system, but that is not clear enough to assume.

Current destination: jobicy.com · HTTPS

No additional required application step is clear in the available listing text. This does not mean the external application is one-click or friction-free.

Application effort is estimated from visible listing and source details. Optional steps are kept separate from mandatory ones, and the external form may contain additional requirements that are not visible here.

Application safety context

Application safety check

Basic application-safety context available

The current application destination has a basic transport-safety signal such as HTTPS. This does not verify the employer, vacancy, recruiter or application process.

Evidence checked: Source provenance · Application destination · Listing wording

Observable transport-safety signals

  • The available application destination uses HTTPS.
Before you share money or sensitive information
  • Confirm the vacancy on the employer’s official careers site when practical, especially if a recruiter contacts you outside the listed application path.
  • Check that recruiter email domains and application destinations are consistent with the employer or an identifiable recruiting provider.
  • Do not pay application, processing, training or equipment fees merely to be considered for a job.
  • Do not send cryptocurrency, gift cards, online-banking credentials or PINs as part of an application.
  • Treat unusually fast offers or interviews conducted only through informal messaging channels as reasons to verify the employer independently.

This is a limited safety screen, not employer verification and not a fraud determination. Never send money, cryptocurrency, passwords or sensitive banking credentials merely because a listing appears on a job platform.

Original listing details

The section below comes from the listing source. The decision sections above use the job’s structured pay, location, qualification, mobility and application details to give you additional context.

Counterpart Health is an AI‑powered physician enablement platform that delivers clinical insights to providers at the point of care. Our flagship product, Counterpart Assistant, is embedded into clinicians’ workflows and integrates with EHR systems, helping care teams drive value-based outcomes, close care gaps, and proactively manage chronic disease. As we grow our data ecosystem, expanding across legacy interoperability networks, QHIN/TEFCA connectivity, and direct HIE integrations, we need rigorous analytical ownership to ensure the clinical data powering our platform is complete, reliable, and actionable.

You will serve as the Subject Matter Expert (SME) for clinical data completeness and effectiveness at Counterpart Health. Sitting within the Data Products pillar, this role owns the end-to-end understanding of our clinical data lifecycle: where data comes from, where it breaks down, and how each vendor or integration pathway performs across our customer markets. Your analysis will directly shape vendor strategy, facility targeting, and data pipeline investments, thus ensuring that the clinical evidence our care teams depend on is consistently available and trustworthy.

As a Data Analyst, you will:

  • Proactively identify and monitor which healthcare facilities consistently generate high-quality, usable clinical documents (e.g., EHRs, discharge summaries, procedure notes) to precisely locate and quantify data gaps.
  • Conduct deep-dive analyses by mapping and correlating facility-specific data across disparate sources like structured claims, clinical care summaries (CCDAs), and ADT messages to uncover systematic patterns of missingness, latency,
  • Experience with TEFCA/QHIN frameworks and evolving national interoperability standards.
  • Familiarity with vendor-specific data exchange platforms (e.g., Bamboo Health, HSX, Particle Health, Kno2).
  • Background in value-based care, population health, or clinical data operations.
  • Experience with claims-clinical data reconciliation (e.g., matching EOBs to clinical encounter records).
  • Comfort working with Python or similar tools for data manipulation and automation.
  • or incongruence in clinical records.
  • Establish and maintain clear, transparent reporting on ADT coverage across key geographic, organizational, and technological dimensions (e.g., by county, facility, and underlying EMR system).
  • Based on rigorous analysis of data flow and quality, recommend and guide the implementation of optimal technical configurations for existing data vendors (e.g., Bamboo Health, PCC, Experian, HSX).
  • Conduct comprehensive evaluations and proof-of-concepts for potential new data integration technologies (e.g., Kno2 vs. Particle Health) to assess viability, quality improvements, and strategic fit.
  • Systematically determine the existence and completeness of documentation associated with specific patient visits or encounters.
  • Develop a data-driven framework for prioritizing facility targets for direct data acquisition, assessing impact, cost-effectiveness, and technical feasibility.
  • Inform and guide vendor strategy around national initiatives such as TEFCA and QHIN adoption, ensuring Counterpart Health is positioned for compliant, high-quality data exchange.
  • Partner cross-functionally with Product Managers to define data requirements, Engineers to implement reliable pipelines, and Clinical teams to validate data quality and clinical utility.
  • Act as a critical liaison to identify and remove operational and technical bottlenecks, ensuring a predictable, scalable, and reliable clinical data flow across all customer markets.

You should get in touch if you have:

  • 2+ years of hands-on data analytics experience, with direct exposure to healthcare data interoperability
  • Strong hands-on experience with healthcare data standards: HL7, CCDA, and ADT messages.
  • Proficiency in SQL and comfort working with large, complex datasets (claims, clinical logs, interoperability data).
  • Background in analyzing interoperability networks (e.g., Carequality, CommonWell, eHealthExchange) or HIE integrations.
  • Skilled at data visualization and able to present complex findings to both technical and non-technical stakeholders.
  • Strong investigative mindset, i.e., you enjoy digging into the “why” behind missing data and diverging metrics.
  • Self-directed and able to manage multiple analytical projects (vendor comparisons, visit-level reconciliation) without constant supervision.

Preferred Qualifications:

  • Experience with TEFCA/QHIN frameworks and evolving national interoperability standards.
  • Familiarity with vendor-specific data exchange platforms (e.g., Bamboo Health, HSX, Particle Health, Kno2).
  • Background in value-based care, population health, or clinical data operations.
  • Experience with claims-clinical data reconciliation (e.g., matching EOBs to clinical encounter records).
  • Comfort working with Python or similar tools for data manipulation and automation.

Benefits Overview:

  • Financial Well-Being: Our commitment to attracting and retaining top talent begins with a competitive base salary and equity opportunities. Additionally, we offer a performance-based bonus program, 401k matching, and regular compensation reviews to recognize and reward exceptional contributions.
  • Physical Well-Being: We prioritize the health and well-being of our employees and their families by providing comprehensive medical, dental, and vision coverage. Your health matters to us, and we invest in ensuring you have access to quality healthcare.
  • Mental Well-Being: We understand the importance of mental health in fostering productivity and maintaining work-life balance. To support this, we offer initiatives such as No-Meeting Fridays, monthly company holidays, access to mental health resources, and a generous flexible time-off policy. Additionally, we embrace a remote-first culture that supports collaboration and flexibility, allowing our team members to thrive from any location.
  • Professional Development: Developing internal talent is a priority for Clover. We offer learning programs, mentorship, professional development funding, and regular performance feedback and reviews.

Additional Perks:

  • Employee Stock Purchase Plan (ESPP) offering discounted equity opportunities
  • Reimbursement for office setup expenses
  • Monthly cell phone & internet stipend
  • Remote-first culture, enabling collaboration with global teams
  • Paid parental leave for all new parents
  • And much more!

About Counterpart Health: In 2018, Clover Health set out to do something unprecedented: build a clinically intuitive, AI-enabled solution that fits within physicians' workflows to help support the earlier diagnosis and management of chronic conditions.

Years later, that vision is a reality, with thousands of practitioners using Counterpart Assistant during patient visits to improve disease management, reduce medical expenses, and drive success in value-based care.

With an exceptional team of value-based care and technology experts, Counterpart Health is driving value-based care at the speed of software.

Counterpart Health is a subsidiary of Clover Health. From Clover’s inception, Diversity & Inclusion have always been key to our success. We are an Equal Opportunity Employer and our employees are people with different strengths, experiences, perspectives, opinions, and backgrounds, who share a passion for improving people's lives. Diversity not only includes race and gender identity, but also age, disability status, veteran status, sexual orientation, religion and many other parts of one’s identity. All of our employee’s points of view are key to our success, and inclusion is everyone's responsibility.

#LI-REMOTE

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. We are an E-Verify company.

Final pay is based on several factors including but not limited to internal equity, market data, and the applicant’s education, work experience, certifications, etc.

A reasonable estimate of the base salary range for this role is:

$77,000—$100,000 USD

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