Job intelligence
Senior Data Scientist - Personalization & Predictions
Bloomreach
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.
Fast read
Opportunity DNA
The listing is still missing enough detail that the most useful next step is to resolve the open questions before making a strong comparison.
Current comparable position is around the 35th percentile.
The work arrangement can be assessed, although it is not among the most flexible patterns detected.
The listing does not make the minimum education or experience threshold clear enough yet.
Sponsorship and relocation support are not clear from the current listing.
Part of the application route can be assessed, but the full external process may contain additional steps.
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
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
No major trade-off is stated clearly in the information available here. Employment terms outside the listing may still matter.
Questions worth asking before you invest more time
- Confirm which countries employees may work from and whether payroll-country, timezone or office-attendance restrictions apply.
- 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 Analyst
Tremendous · LATAM, Canada, USA
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
Different angle: Different country
Senior Data Scientist
Trainline · London
Why it is nearby: Same seniority band · Same employment type · Recently posted
Different angle: Different work arrangement
Staff Machine Learning Engineer - Pricing
tem · United Kingdom
Why it is nearby: Same seniority band · Same employment type · Recently posted
Different angle: Different country · Different work arrangement
Senior Applied AI Engineer
Jupus · Cologne
Why it is nearby: Same seniority band · Same employment type · Recently posted
Different angle: Different work arrangement
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.
200 most recent current roles sampled for the disclosure measures below.
Distinct employers in the bounded current sample, not an estimate of all employers hiring in the market.
Current sampled roles stating at least four of the five Core Decision Facts.
Requires a numeric amount, explicit ISO currency and supported pay period.
Listings with explicit enough remote, hybrid or on-site evidence to classify.
Missing deadline evidence remains unknown and is not interpreted as an open-ended application window.
Currencies with explicit pay evidence in the sample: USD (47) · EUR (15) · GBP (2) · CAD (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.
Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.
Uses only roles where a country is known. Roles without country evidence are excluded from this denominator.
A much stricter subset: only listings with explicit worldwide-remote evidence remain.
Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.
Shows the subset with enough stated evidence for a more informed first comparison.
Requires amount, explicit ISO currency and a supported pay period. Missing pay evidence remains unknown.
Only same-currency opportunities with usable annualized pay enter this comparison. Other currencies are not converted or treated as lower.
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 1250 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 33% of the bounded current role sample does the same.
Compensation counts only when amount, ISO currency and supported pay period are all known.
Pay disclosure is limited in the current role sample.
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.
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.
Usable advertised compensation is available.
Variable compensation is mentioned; verify amount, formula, target and eligibility.
Equity or long-term incentive language is mentioned; verify grant type, vesting and valuation basis.
Retirement or pension benefits are mentioned; verify employer contribution and vesting.
Health-benefit language is mentioned; verify coverage, dependants and employee cost.
Paid-leave language is mentioned; verify the exact entitlement and carry-over rules.
A work-arrangement signal is available; verify schedule details before relying on it.
Relocation support not established
Sponsorship not established
A review cycle is mentioned; verify timing and whether compensation can change at that review.
Questions worth taking into the offer conversation
- What retirement or pension contribution does the employer provide?
- What health coverage is included and what costs remain with the employee?
- 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?
- 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.
European occupation references
This service uses the ESCO classification of the European Commission.
U.S. occupation references
- Data Scientists 15-2051.00
- Computer and Information Research Scientists 15-1221.00
- Social Science Research Assistants 19-4061.00
- Atmospheric and Space Scientists 19-2021.00
- Bioinformatics Scientists 19-1029.01
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.
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
Senior Backend Engineer II & III (.NET)
M Kopa · London
same seniority band · same employment typeSenior Product Manager
Motorway · London
same seniority band · same employment typeSenior Platform Engineer
Trainline · London
same seniority band · same employment typeAdjacent-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
Associate Data Scientist
Jerry · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedApplied AI Engineer
Bjak · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedStretch direction
Lead Data Analyst
Liftoff · USA
Similar work arrangement · Same employment type · Recently postedStaff Data Engineer
Jobber · Canada
Similar work arrangement · Same employment type · Recently postedThese 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?
Databricks is one of the signals this listing shares with skills appearing often across current Data & AI roles opportunities.
Skills named in this listing
Shared with the current career sample
- Databricks Seen in 22 sampled listings
- Google Cloud Seen in 19 sampled listings
- Large Language Models Seen in 36 sampled listings
- Python Seen in 76 sampled listings
Combinations also appearing together
- Python + SQL appeared together in 53 sampled listings
- Large Language Models + Python appeared together in 24 sampled listings
- Databricks + Python appeared together in 17 sampled listings
Additional signals in this listing: Generative AI
Application edge
- If these skills match your background, prepare one concrete example that shows how you used Databricks, Google Cloud, and Generative AI 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; 119 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.
Databricks
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.
Google Cloud
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.
Generative AI
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.
Large Language Models
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.
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.
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
A closer look at Senior Data Scientist - Personalization & Predictions at Bloomreach points most strongly to pay has a useful comparison point, 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.
Pay has a useful comparison point
Among 34 current comparable salaries in EUR, the normalized annual midpoint is around the 35th 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 76/100.
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?
Uses the explainable High Pay Score within the job’s current occupation/seniority/currency comparison sample.
Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.
The configured source supplied structured salary fields, a usable currency and a focused comparison value.
The source posting date is today.
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
No specific caution is supported by the currently available evidence. This does not prove that none exists.
Still unknown
- Visa sponsorship is not established by the available listing data.
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.
Comparable disclosed-pay evidence places this job at about 35 / 100 within its current occupation/seniority sample.
- 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.
The source provides structured salary information with a comparatively focused range, improving the usefulness of pay comparisons.
The source posting date is today.
Compensation intelligence
How competitive is this pay?
Below many comparable disclosed salaries
The annualized midpoint is below the current comparable median but remains within the sample’s lower-to-middle range.
The highlighted band is the middle 50% of the current comparable sample after the outlier guard. The dark marker is this job’s annualized salary midpoint.
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 Bloomreach
Good 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.
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
Bloomreach — current opportunity snapshot
Employer Evidence Profile
How often this employer’s current visible sampled vacancies state decision-critical information. These percentages describe evidence coverage, not employer quality.
Current sampled listings with advertised compensation evidence.
Current sampled listings whose work arrangement is clearer than unknown.
Current sampled listings with a supported country signal.
Current sampled listings with an explicit closing time.
Current sampled listings with a usable posting date.
Current sampled listings that explicitly indicate confirmed, possible or unavailable sponsorship evidence.
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: Software engineering (7) · Sales (7) · Data & AI (2)
Visible seniority mix: Senior / lead (20) · Leadership (2)
Current employment-type mix: Full time (16) · Contract (1)
Most visible hiring countries in this sample: Slovakia (8) · Czechia (4) · United Kingdom (2)
Other current roles from this employer
Technical Writer II
Czechia
Seniority not clearly specified · Remote — restrictions unclearQuality Assurance Engineer II
Slovakia
Senior / lead · Remote — restrictions unclearStaff Software Engineer
Europe
Senior / lead · Region-restricted remoteStaff DevOps Engineer
Czechia
Senior / lead · Remote — restrictions unclearThese are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.
Current disclosed salary medians by currency
- USD 3,000 median · 10 disclosed salaries
- CZK 1,268,375 median · 8 disclosed salaries
- EUR 46,800 median · 5 disclosed salaries
Questions worth asking this employer
- 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
Remote with some uncertainty or restrictions
Why this score?
- The role is remote, but the exact applicant-location restrictions are not clear.
Flexibility signals detected
- The description reinforces broad location independence.
- The description indicates scheduling flexibility that can support location independence.
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.
The available listing details do not contain a clear enough sponsorship statement.
The available listing details do not contain a clear enough relocation statement.
Tradeoff check
What’s the catch?
No obvious trade-off appears in the available job details. That does not mean the role has no drawbacks, so the original listing and employment terms are still worth reading carefully.
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.
(Senior) AI Engineer (m/f/d) – Remote
MAIA · Berlin
Remote — restrictions unclearWhy comparable: Same seniority band · Similar work-location arrangement · Same employment type
Machine Learning Scientist
Mitek Systems · Remote — Worldwide
Worldwide remoteWhy comparable: Same seniority band · Similar work-location arrangement · Same employment type
Senior AI Engineer | Construction Tech (w/m/d)
Right Search · Munich
On-site / hybridWhy comparable: Same seniority band · Recently posted
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.
Bloomreach is building the world’s premier agentic platform for personalization.We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey.
- We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses.
- We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey.
- We're designing the future of autonomous marketing, taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do.
And we're building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora.
You'd be joining the Artificial Intelligence team. We own the algorithmic core of the platform: Predictions, Contextual Personalization, contextual bandits, autosegmentation, and the agentic workflows behind Loomi. We work with behavioural data at terabyte scale, across 1,400+ customers, in production, every day. We are currently allowing flexibility for our employees to work from anywhere for the respective region (Central & Eastern Europe) or we are happy to meet you in our offices in Bratislava (Slovakia) or Brno, Prague (Czechia) on a full-time basis.
The mission
You find the signal in how 1,400 brands' customers actually behave — and you prove it moved a business metric. Your models decide which customers are predicted to churn, which segments form themselves, which offer a shopper sees, and whether the discount changed anything or was going to convert anyway.
What you'll actually do
- Frame the problem before modelling it. Most of our highest-impact work arrives as a vague business question, and turning it into something measurable is the first job.
- Work the data at scale. Behavioural data, product catalogues and event streams across BigQuery and Databricks — finding features that carry real predictive signal, not the ones that are easy to compute.
- Build and evaluate models across Predictions and Contextual Personalization: propensity and churn, contextual bandits, autosegmentation, uplift and incrementality.
- Design the evaluation, not just the model. Offline metrics, backtests, and the A/B design that decides whether this ships. You own the question "how would we know if this is worse?"
- Bring methods in from outside and judge them honestly — read the literature, run the quick PoC, and tell a real result from a well-marketed one.
- Hand off cleanly to ML Engineering. You own the model and the evidence; they own making it survive production. That handoff is a document and a conversation, not a notebook over a wall.
- Explain your results to people who aren't data scientists — Product, Engineering leadership, and sometimes customers.
What success looks like after 12 months
- Two models you built are in production and you can name the business metric each one moved.
- A question the team was arguing about is settled, with evidence, and your writeup is what people link to.
- ML Engineering describes your handoffs as easy.
This role bends in three directions
We'd rather shape it around you than the other way round.
- Modelling & data science — features, experiments, and whether the number means anything.
- ML product engineering — you own an ML-powered feature end to end and the ML part is what makes it interesting.
- Platform & MLOps — pipelines, serving, deployment, observability, inference cost.
Most people lean one way and dip into the others. This opening is centered on the first. If you'd rather own the serving path, latency and reliability, our our Senior AI/ML Engineer opening (in Czechia or Slovakia) is the better fit, and applying to both is fine.
What you'll need
- 5+ years building ML models that shipped and were used by someone other than you — in industry, not only in research or coursework.
- Strong Python and genuinely strong SQL. You should be comfortable being handed a warehouse and finding your own way around it.
- Solid grounding in classical ML — tree-based models, regression, classification, clustering — and the judgement to know when the simpler model is the right answer.
- Real rigour on experiment design and evaluation. You know why a metric moved, and when it didn't move for the reason everyone assumes.
- Comfort on a cloud data platform — we work in GCP (BigQuery) and Databricks, but the principles transfer.
- A quantitative degree, or equivalent practical depth.
- Working English, written and spoken.
Plus real depth in at least one of:
- Causal inference and uplift modelling — separating who converts because of an intervention from who would have converted anyway.
- Contextual bandits, sequential decision-making, or off-policy evaluation.
- Ranking, recommendation or information retrieval.
- LLM evaluation, or applied work with the GenAI stack.
Also good: you use agentic coding tools daily and have a view on where they help and where they quietly don't. We build agents for a living, and people who use them tend to have better instincts about them.
#LI-KP1
The pay range actually offered will take into account a variety of potential factors considered in compensation, including but not limited to skills, qualifications, geographic location, accomplishments, experience, credentials, internal equity and business needs, and may vary from the range listed above.
Base Salary Range
€50.290—€62.900 EUR
More things you'll like about Bloomreach:
Culture:
-
A great deal of freedom and trust. At Bloomreach we don’t clock in and out, and we have neither corporate rules nor long approval processes. This freedom goes hand in hand with responsibility. We are interested in results from day one.
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We have defined our 5 values and the 10 underlying key behaviors that we strongly believe in. We can only succeed if everyone lives these behaviors day to day. We've embedded them in our processes like recruitment, onboarding, feedback, personal development, performance review and internal communication.
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We believe in flexible working hours to accommodate your working style.
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We work virtual-first with several Bloomreach Hubs available across three continents.
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We organize company events to experience the global spirit of the company and get excited about what's ahead.
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We encourage and support our employees to engage in volunteering activities - every Bloomreacher can take 5 paid days off to volunteer*.
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The Bloomreach Glassdoor page elaborates on our stellar 4.7/5 rating. The Bloomreach Comparably page Culture score is even higher at 4.9/5
Personal Development:
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We have a People Development Program - participating in personal development workshops on various topics run by experts from inside the company. We are continuously developing & updating competency maps for select functions.
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Our resident communication coach Ivo Večeřa is available to help navigate work-related communications & decision-making challenges.*
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Our managers are strongly encouraged to participate in the Leader Development Program to develop in the areas we consider essential for any leader. The program includes regular comprehensive feedback, consultations with a coach and follow-up check-ins.
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Bloomreachers utilize the $1,500 professional education budget on an annual basis to purchase education products (books, courses, certifications, etc.)*
Well-being:
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The Employee Assistance Program -- with counselors -- is available for non-work-related challenges.*
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Subscription to Calm - sleep and meditation app.*
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We organize ‘DisConnect’ days where Bloomreachers globally enjoy one additional day off each quarter, allowing us to unwind together and focus on activities away from the screen with our loved ones.
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We facilitate sports, yoga, and meditation opportunities for each other.
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Extended parental leave up to 26 calendar weeks for Primary Caregivers.*
Compensation:
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Restricted Stock Units or Stock Options are granted depending on a team member’s role, seniority, and location.*
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Everyone gets to participate in the company's success through the company performance bonus.*
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We offer an employee referral bonus of up to $3,000!
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We reward & celebrate work anniversaries -- Bloomversaries!*
(*Subject to employment type. Interns are exempt from marked benefits, usually for the first 6 months.)
Excited? Join us and transform the future of commerce experiences!
If this position doesn't suit you, but you know someone who might be a great fit, share it - we will be very grateful!
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Listing provenance
Where did this job come from?
See where this vacancy came from and whether more than one current source can still support it. Source names help with traceability and attribution; they are not endorsements or guarantees.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
- Continuity
- One recent renewable source
- Source-class independence
- One renewable source class
- Last source observation
- Observed very recently
This records when High Paid Job last observed the vacancy in source evidence. It confirms source presence, not that the employer edited the vacancy at that time.
- 1 enabled source recently observed this vacancy.
Source confidence is about traceability and continuity. It is separate from application safety and should not be read as an employer reputation rating.
The vacancy is supplied by an external job publisher. Source information helps show where the listing came from; it is not a guarantee about the employer or vacancy.
Listing source: Jobicy. Destination: jobicy.com. The application opens in a new tab so you can keep this report open.