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Principal Data Scientist, User Ecosystem

Reddit

Location: USA Advertised pay: USD 313,000–365,100 / yearly Work arrangement: Region-restricted remote Employment: Full Time Posted: November 8, 2026 Freshness: Posted today Source check: Observed very recently
Disclosure4 of 5 core facts statedReview uncertainties
Last source observationObserved very recentlyObservation is not employer confirmation.
Application destinationjobicy.comReview the application route and source evidence in the full report below.

Before relying on the listing: Confirm Application closing time with the employer or source. See verification questions

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 positionAbove the current upper quartile61 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 alternatives1245 current same-family rolesCurrent 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.

Fast read

Opportunity DNA

There is a useful advantage here: pay compares strongly with similar current roles. Still, location rules could change the fit could change the fit.

May appeal in aCompensation-led search
PayStrong current position

Around the 99th percentile within 61 comparable USD salary observations.

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
  • Advertised location
  • Employment type

What to verify next

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

Advertised location is not proof of work authorization, sponsorship, or legal eligibility. Unknown information is not a negative score; verify those questions separately.

Decision levers

What could make or break the fit?

Reasons to look closer

  • Pay compares strongly with similar current roles: The annualized midpoint is around the 99th percentile among 61 comparable USD salary observations.

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.

Senior Data Engineer

Worldly · USA

USD 135,000–165,000 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same seniority band · Same country · Similar work arrangement

About 56% lower advertised midpoint

Engineering Manager, Machine Learning (Safety)

Discord · USA

USD 272,000–340,000 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same seniority band · Same country · Similar work arrangement

About 10% lower advertised midpoint

Senior AI Engineer, Voice Platform

ClickUp · USA

USD 200,000–250,000 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same seniority band · Same country · Similar work arrangement

About 34% lower advertised midpoint

Data Scientist, Corporate

YipitData · USA

USD up to 170,000 / year Region-restricted remote 4/5 core facts

Why it is nearby: Same seniority band · Same country · Similar work arrangement

About 50% lower advertised midpoint

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 roles1,245

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

Employers represented128

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 stated30%

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

Work arrangement stated92%

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 (50) · EUR (6) · GBP (4) · CHF (1). 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 0 / 200 0%

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

Require worldwide remote evidence 9 / 200 5%

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

Keep this advertised salary floor in the same currency 5 / 49 10%

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

Require a remote-listed arrangement 47 / 200 24%

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

Require at least four Core Decision Facts 55 / 200 28%

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

Require usable compensation disclosure 60 / 200 30%

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

Stay in the same stated country 41 / 88 47%

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

Stay around the same seniority band 184 / 200 92%

Includes roles whose seniority is genuinely unspecified rather than assuming they belong to another level.

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 1245 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 30% 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 sample30%

Pay disclosure is limited 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 313,000–365,100 / yearListing evidence only.
Current comparable medianUSD 175,50045 current sampled roles
Current upper quartileUSD 246,700Current 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
  • handle data samples
  • integrate gender dimension in research
  • deliver visual presentation of data
  • scientific literature
  • promote the participation of citizens in scientific and research activities
  • perform data cleansing
  • manage intellectual property rights
Context-dependent ESCO skills
  • MDX
  • scientific computing
  • digital curation
  • integrate ICT data
  • 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.

handle data samplesESCO · Essential · Listing mention unknown
integrate gender dimension in researchESCO · Essential · Listing mention unknown
deliver visual presentation of dataESCO · Essential · Listing mention unknown
scientific literatureESCO · Essential · Listing mention unknown
promote the participation of citizens in scientific and research activitiesESCO · Essential · Listing mention unknown
perform data cleansingESCO · Essential · Listing mention unknown
manage intellectual property rightsESCO · Essential · Listing mention unknown
MDXESCO · Optional · Listing mention unknown
scientific computingESCO · Optional · Listing mention unknown
digital curationESCO · Optional · Listing mention unknown
integrate ICT dataESCO · 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.

Career move map

What sits one step away?

This listing is currently read as Senior / lead. Nearby roles one visible seniority step away can help you judge whether to widen the search, stretch upward or compare the responsibilities more carefully.

Broader-entry direction

Mid-career

FBS Associate Data Engineer

Capgemini Technology Services · Remote — Worldwide

Similar work arrangement · Same employment type · Recently posted

Stretch direction

Leadership

Staff Data Analyst, Marketing

1Password · Canada, USA

Same country · Similar work arrangement · Same employment type Advertised midpoint is about 46% lower
Leadership

Staff Data Scientist

hims & hers · USA

Same country · Similar work arrangement · Same employment type Advertised midpoint is about 38% lower

These are live roles one visible seniority step away in the same broad occupation family. They can reveal nearby options, but they are not a guaranteed promotion path and do not account for your personal experience.

Skill bridge

What does this role connect to?

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

Skills named in this listing

Machine Learning

Shared with the current career sample

  • Machine Learning Seen in 50 sampled listings

Application edge

  • If these skills match your background, prepare one concrete example that shows how you used Machine Learning 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; 118 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

Machine Learning

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

A closer look at Principal Data Scientist, User Ecosystem at Reddit points most strongly to the advertised pay can be placed in context, remote flexibility can be weighed properly, and the application route gives a few useful clues. Those signals shape the practical upside and the questions still worth asking.

The advertised pay can be placed in context

Among 61 current comparable salaries in USD, the normalized annual midpoint is around the 99th percentile. This compares advertised pay in the same currency and does not include every element of total compensation.

Remote flexibility can be weighed properly

The work-location pattern is “Remote with some uncertainty or restrictions”, with Remote Freedom at 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

The opportunity currently has 1 renewable source path across 1 source classes. Multiple independent paths can strengthen continuity, but they are not a substitute for checking the application destination.

How this analysis is assembled

The brief pulls together the parts of the vacancy that can be compared reliably today. Gaps in the listing remain visible instead of being filled with assumptions.

Analysis evidence coverage

How much analysis can the current evidence support?

100%Strong analysis evidence coverage
100%
Current-sample pay position99 / 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

  • Advertised pay is above much of the current comparable disclosed-salary sample.

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

Strong pay with stated barriers to weigh

Pay compares strongly, but qualification or location constraints are also visible. Higher pay does not erase those practical requirements.

Current-sample pay position

Comparable disclosed-pay evidence places this job at about 99 / 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.

Strong current-sample pay position

The annualized salary midpoint is at or above about 99% of the current comparable disclosed-salary sample.

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.

Exceptional current-sample pay

Its annualized salary midpoint is at or above about 99% of the current comparable disclosed-salary sample.

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?

99/100

Exceptional pay in current sample

99%
Comparison familyData & AI roles · Senior / lead
Comparable salaries61
Current-sample medianUSD 190,000
Middle 50% of sampleUSD 160,000–232,056
Position in sampleAt or above about 99%
Comparison geographySame country (US)
Pay positionAbove the current upper quartile

The annualized midpoint is above the 75th 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 Reddit

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.

64/100
64%
Salary disclosure55% · 30 of 55 sampled listings
Range qualityMostly focused or specific pay information
Bonus wording32 current listings
Equity wording32 current listings
Benefits wording39 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

Reddit — current opportunity snapshot

Current opportunities visible55
Salary disclosure55%
Remote-policy evidence coverage100% · 55 of 55 sampled listings
Remote share of known arrangements89%
Worldwide-remote share18%
Known hiring countries6
Sponsorship evidence coverage0% · 0 of 55 sampled listings
Explicit sponsorship outcomes0 confirmed · 0 possible · 0 unavailable
Pattern sample55 of 55 · 100% coverage
Current role-family breadth8
Stated closing-date coverage18%
Relocation evidence coverage0% · 0 explicitly offered
Posted within 7 days38% 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.

Location71% of sampled current listings

Current sampled listings with a supported country signal.

Application timing18% 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: Data & AI (15) · Product (8) · Software engineering (8)

Visible seniority mix: Early-career (2) · Senior / lead (34) · Leadership (5)

Current employment-type mix: Full time (36) · Contract (13)

Most visible hiring countries in this sample: United States (26) · United Kingdom (5) · Canada (4) · Netherlands (2)

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 260,450 median · 30 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 +46% midpoint

Data Engineer (L5) - Ads

Netflix · Remote — Worldwide

Worldwide remote

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

About +9486% midpoint

Staff Machine Learning Engineer

MoonPay · London - Hybrid

On-site / hybrid

Why comparable: Same seniority band · Same employment type

Check: The alternative has an unusually broad advertised salary range.

About +15237% midpoint

AI Engineer

Jobgether · UK

On-site / hybrid

Why comparable: Same employment type · Recently posted

Check: Seniority is not explicit in the alternative listing. Different country from the current job.

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.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is a complex consumer ecosystem where users, content, communities, and conversations interact over time. We are looking for a very senior data science thought leader to shape how Reddit understands and improves that ecosystem for the user / consumer flywheel.

This role will define the measurement, modeling, and experimentation strategy for major Consumer questions: how users discover value, form habits, and deepen engagement; how we understand and serve user intent; how content and communities evolve; and how our systems create durable value for users, contributors, communities, and Reddit.

The ideal candidate will bring deep expertise in one or more areas of consumer science, such as:

  • Recommender systems and information retrieval
  • User modeling, personalization, lifecycle, LTV, or optimization
  • Content, community, or ecosystem modeling
  • Knowledge graphs and representations of users, content, and communities
  • Causal inference, experimentation, and long-term consumer measurement

You will partner with leaders across Product, Engineering, Research, and Community to turn ambiguous consumer problems into clear scientific questions, durable analytical systems, and decisions that improve Reddit at scale.

What you’ll do

  • Set the scientific direction for high-impact Consumer problems spanning discovery, relevance, personalization, user growth, retention, content, and communities.
  • Build a durable understanding of users, their intent, their needs, and the behaviors that lead to lasting value
  • Develop models and frameworks that represent users, content, communities, and their relationships over time for use in systems that operate at scale
  • Determine how to measure consumer and ecosystem health when objectives compete and short-term engagement may differ from long-term value.
  • Set learning agendas and steer experimentation strategy to distinguish durable improvement from temporary metric movement.
  • Build state-of-the-art measurement systems to evaluate heterogeneous effects across user personas, acquisition cohorts, platforms, content types, and community stages, and guide their actionability in production environments
  • Ensure coherence around ecosystem interactions including feedback loops, selection effects, interference, distribution shift, content supply, and other ecosystem risks.
  • Translate complex technical findings into clear product and business decisions.
  • Develop exceptional scientists through mentoring and influence data science org health and direction

Requirements

  • Deep expertise in at least one relevant area, with the breadth and curiosity to work across adjacent domains.
  • A deep understanding of how to model and optimize systems involving users, content, communities, and feedback loops.
  • Ability to frame and lead the most ambiguous questions, identify the most important uncertainties, and develop a rigorous path from evidence to action.
  • Exceptional technical judgment across model design, objective selection, validation, experimentation, and production tradeoffs.
  • Advanced knowledge of modern machine-learning methods for behavioral and content data, including representation learning and sequential or contextual models. Experience with deep-learning frameworks such as PyTorch or JAX.
  • Experience working across Product, Engineering, Research, and other partner teams.
  • Excellent written and verbal communication, with the ability to influence senior stakeholders and explain technical ideas clearly.
  • Significant experience applying data science, machine learning, statistics, experimentation, or causal inference to complex consumer products.

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$313,000—$365,100 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

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