Data Scientist

Andersen is hiring a Data Scientist in Poland for a project developing a large-scale media intelligence platform and delivering AI-powered audience analytics solutions.

The company is a global technology provider delivering data analytics and AI-powered solutions that help organizations better understand customer behavior, optimize marketing performance, and make informed business decisions. By transforming large volumes of data into actionable insights, it enables enterprises to improve audience engagement, measure the effectiveness of their initiatives, and enhance decision-making. The company works with a diverse range of customers, supporting them in navigating an increasingly data-driven and rapidly evolving digital landscape.

The project is focused on developing a large-scale media intelligence platform that analyzes consumer engagement across TV, digital, and connected devices. It leverages real-time, consented data to deliver audience insights, content analytics, and data-driven solutions for media and advertising.

Responsibilities:

- Owning end-to-end delivery of significant data science projects - from problem scoping and approach design through to production deployment.

- Making sound, independently-reasoned decisions on methodology, model selection, and evaluation; documenting them clearly in technical solution documents covering problem statement, approach, metrics, and timeline.

- Leading solution design for your own initiatives.

- Breaking down complex epics into well-scoped user stories with clear acceptance criteria, adopting DataOps and MLOps best practices throughout - experiment tracking, pipeline orchestration, model monitoring, and reproducibility.

- Building production-quality Python and PySpark code on Databricks - well-tested, documented, and reusable - and implement advanced ML and AI-powered workflows including entity resolution, probabilistic record linkage, embedding-based matching, semantic similarity, and LLM-augmented pipelines.

- Developing and maintaining reusable tools, libraries, and documentation that improve team efficiency and technical standards.

- Conducting code reviews with constructive, specific feedback that raises the bar.

- Mentoring junior data scientists on technical execution, code quality, and career development.

- Leading internal talks or workshops on ML topics.

- Collaborating cross-functionally with product, engineering, and operations - translating business requirements into technical specifications, partner with data engineering on scalable pipeline design, and participate in cross-functional design reviews and working groups.

Must-haves:

- Hands-on experience in Data Science, including ownership of complex, multi-sprint projects for 3+ years.

- Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, or another quantitative field (Master's degree preferred).

- Advanced proficiency in Python, including writing production-quality, well-tested, and well-documented code.

- Strong experience with SQL and PySpark, including processing datasets at billion-row scale.

- Hands-on experience with Databricks, including Workflows, Delta Lake, and job orchestration.

- Working knowledge of AWS or Google Cloud Platform (GCP).

- Strong foundation in Machine Learning, including regression, classification, clustering, model evaluation, and experimental design.

- Experience with MLOps practices, including experiment tracking, Airflow-based pipeline orchestration, and reproducible model deployment.

- Familiarity with modern AI technologies, including Retrieval-Augmented Generation (RAG), LLM-based applications, vector databases, and semantic search.

- Strong written and verbal communication skills, including technical documentation, user story creation, and cross-functional collaboration.

- Level of English - from Intermediate+ and above.

Nice to have:

- Knowledge graph construction, entity resolution, or semantic data modeling (RDF, OWL, SPARQL, or equivalent).

- Experience with probabilistic record linkage, identity graph approaches, and embedding-based entity matching at scale.

- Experience with causal inference methods, including A/B testing, synthetic control, and uplift modeling.

- Experience with deduplication, data enrichment, or web-to-TV linkage problems.

- Background in media, ad tech, or measurement specifically: TV viewership (ACR/STB data), digital audience modeling, cross-platform measurement (linear + CTV/OTT), identity resolution in privacy-constrained environments.

- Familiarity with the measurement/identity vendor landscape: Nielsen, Comscore, LiveRamp, The Trade Desk.

Reasons why this job would be interesting to you:

- Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc..

- The opportunity to change the project and/or develop expertise in an interesting business domain.

- Job conditions - you can work both fully remotely and from the office or can choose a hybrid variant.

- Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee.

- The opportunity to earn up to an additional 1,000 EUR per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.

- Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.

- Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).

- Certification compensation (AWS, PMP, etc).

- Referral program.

- Private health insurance and sports compensation, depending on the type of employment.

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https://andersenlab.com/privacy-policy/pl

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