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The Role
This is an ownership driven data science position within a scaled, globally distributed hub focused on bringing algorithms to production. The work spans traditional machine learning, deep learning, GenAI, optimization, and statistical modeling. Methods are chosen based on the problem, not the trend. The scope covers high impact business domains including retail, media, digital commerce, supply chain, R&D, and productivity.
This is not a research only role. The expectation is to understand the business problem deeply, build the right model, and see it through to reliable production deployment.
For candidates
The market is full of noise.
Let’s make sure you’re the signal.
You are reading this and thinking: this role is exactly what I want, but my CV and LinkedIn do not show it clearly enough. That is literally what I fix for a living.
Career RE:WORKGet a recruiter who actually fights for you →
CV rewrite
Experience with the full lifecycle of an algorithmic product: not just model building, but deployment, monitoring, and iteration. Familiarity with big data tooling (Databricks, BigQuery, Spark) and exposure to GenAI or optimization methods are genuine advantages, not box ticking requirements.
Working Model and Location
This role is based in Warsaw, Poland, on a hybrid working arrangement. Regular on site presence in Warsaw is expected; full remote is not available for this position.
This is an ownership driven data science position within a scaled, globally distributed hub focused on bringing algorithms to production. The work spans traditional machine learning, deep learning, GenAI, optimization, and statistical modeling. Methods are chosen based on the problem, not the trend. The scope covers high impact business domains including retail, media, digital commerce, supply chain, R&D, and productivity.
This is not a research only role. The expectation is to understand the business problem deeply, build the right model, and see it through to reliable production deployment.
For candidates
The market is full of noise.
Let’s make sure you’re the signal.
You are reading this and thinking: this role is exactly what I want, but my CV and LinkedIn do not show it clearly enough. That is literally what I fix for a living.
Career RE:WORKGet a recruiter who actually fights for you →
CV rewrite
- LinkedIn fix
- Video presentation
- Presented to companies in a way ATS never will.
- Take ownership of a defined business domain and its algorithmic needs from problem framing through to deployed solution
- Partner with product, business, and AI engineering teams to automate and integrate models into live applications
- Analyze large scale datasets (think: processing billions of behavioral signals daily) and translate findings into actionable recommendations
- Define and evolve the algorithmic roadmap for your area of ownership
- Apply machine learning, statistical, optimization, and GenAI techniques to real business problems
- Write production grade code following engineering best practices
- Build resilient, maintainable algorithmic pipelines that hold up over time
- Cloud: Microsoft Azure, Google Cloud Platform, Kubernetes
- Languages: Python, Spark (preferred); SQL for analytical work
- Big data ecosystem: Databricks, BigQuery, Spark
- Dev tools: GitHub, Jira, Confluence (Agile DevOps environment)
- BI tools: PowerBI or Tableau (basic familiarity useful)
- Masters degree in a quantitative field (Statistics, Operations Research, Computer Science, Applied Mathematics, Systems Engineering, Economics) OR a Bachelors or Engineering degree with solid, consecutive data science experience
- At least 2 years of experience delivering production grade data science or algorithmically enabled applications
- Strong Python skills with hands on experience in machine learning, statistical modeling, and optimization
- Solid SQL and analytical skills
- Demonstrated ability to lead problem solving and prioritize across competing demands
- Comfortable working across cross functional teams in a fast moving environment
Experience with the full lifecycle of an algorithmic product: not just model building, but deployment, monitoring, and iteration. Familiarity with big data tooling (Databricks, BigQuery, Spark) and exposure to GenAI or optimization methods are genuine advantages, not box ticking requirements.
Working Model and Location
This role is based in Warsaw, Poland, on a hybrid working arrangement. Regular on site presence in Warsaw is expected; full remote is not available for this position.
Key Skills
Ranked by relevance
machine learning
python
spark
sql
google cloud platform
deep learning
confluence
big data
tableau
devops
cloud
jira
ats
ai
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- Posted
- May 26, 2026
- Type
- Full-time
- Level
- Not Applicable
- Location
- Warsaw
- Company
- WhyHireWrong?
Industries
Technology
Information
Internet
Categories
Engineering
Information Technology
Related Jobs
3 roles aligned with this opportunity
View Job Details
Related
FullStack Developer (C# & Javascript)
2026-05-15
Full-time
Not Applicable
Poland
Technology
Engineering
View Job Details
Related
Tech Lead - PHP
2026-05-13
Full-time
Not Applicable
Poland
Technology
Engineering
View Job Details
Related
Backend Engineer
2026-05-27
Full-time
Not Applicable
Switzerland
Technology
Engineering