Data Scientist (AI)

Location: Poland; fully remote, office-based, or hybrid work options are available.

Company

An international software development and outsourcing company delivering data analytics and AI-powered solutions for customer behavior analysis, marketing optimization, and business decision-making.

What you will do

• Own end-to-end delivery of significant data science projects, from problem scoping and methodology design through production deployment.
• Design and implement production-quality Python and PySpark solutions on Databricks for billion-row datasets.
• Develop machine learning and AI workflows for entity resolution, probabilistic record linkage, embedding-based matching, semantic similarity, and LLM-augmented pipelines.
• Apply DataOps and MLOps practices, including experiment tracking, pipeline orchestration, model monitoring, and reproducibility.
• Create reusable tools, libraries, technical documentation, user stories, and solution designs; conduct code reviews and lead technical workshops.
• Collaborate with product, engineering, operations, and data engineering teams on scalable pipeline design and cross-functional reviews; mentor junior data scientists.

Requirements

• 3+ years of hands-on data science experience owning complex, multi-sprint projects.
• Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, or another quantitative field; a Master's degree is preferred.
• Advanced Python skills with production-quality, well-tested, and well-documented code, plus strong SQL and PySpark experience.
• Hands-on Databricks experience, including Workflows, Delta Lake, and job orchestration.
• Working knowledge of AWS or Google Cloud Platform and strong foundations in regression, classification, clustering, model evaluation, and experimental design.
• Experience with MLOps, Airflow-based orchestration, reproducible deployment, RAG, LLM applications, vector databases, and semantic search; English at Intermediate+ level or above.

Nice to have

• Knowledge graph construction, entity resolution, semantic data modeling, probabilistic record linkage, identity graphs, or embedding-based entity matching.
• Experience with causal inference, A/B testing, synthetic control, uplift modeling, deduplication, data enrichment, or web-to-TV linkage.
• Background in media, ad tech, audience measurement, TV viewership, digital audience modeling, CTV/OTT, or privacy-constrained identity resolution.
• Familiarity with Nielsen, Comscore, LiveRamp, or The Trade Desk.

Culture & Benefits

• Opportunities to work with clients in FinTech, Healthcare, Retail, Telecom, and other industries.
• Possibility to change projects and develop expertise in different business domains.
• Mentoring and onboarding systems supporting professional, financial, and career development.
• Corporate training portal and compensation for professional certifications such as AWS and PMP.
• Private health insurance and sports compensation, depending on the type of employment.
• Employment contract or B2B engagement options, plus referral and corporate activity programs.