Data Scientist - (Knowledge Graph & Identity)

Samba TV; Warszawa; On-site; PLN 260,029 - 334,323; Full time

Job summary

A leading media company in Warsaw is seeking a Data Scientist to contribute to significant data science projects. The role demands expertise in Python and ML techniques, with responsibilities spanning from problem scoping to model deployment. Candidates should have hands-on experience in data science and strong SQL and PySpark skills. The company values diversity and is committed to an inclusive environment.

Qualifications

• 1 to 2 years of hands-on data science experience with complex projects.
• Proficiency in Python and PySpark, capable of handling billion-row datasets.
• Knowledge of MLOps practices such as pipeline orchestration and model monitoring.

Responsibilities

• Contribute to the full lifecycle of data science projects.
• Develop and test Python and PySpark code in Databricks.
• Support MLOps practices, including experiment tracking and pipeline orchestration.

Skills

Python

SQL

PySpark

ML techniques

MLOps

Data Science

Databricks

Education

Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics or related field

Master's degree (preferred)

Tools

Delta Lake

Airflow

Job description

Samba TV tracks streaming and broadcast video across the world with our proprietary data and technology. We are on a mission to fundamentally transform the viewing experience for everyone. Our data enables media companies to connect with audiences for new shows and movies, and enables advertisers to engage viewers and measure reach across all their devices. We have an amazing story with a unique perspective on culture formed by a global footprint of data and AI-driven insights.

As a Data Scientist on Samba TV's Knowledge Graph & Identity team in Warsaw, you will own end-to-end delivery of significant data science projects with minimal guidance. You are a reliable, autonomous contributor with deep expertise in at least one of Samba's core domains - knowledge graphs, identity spine, measurement, or audience modeling - and the technical range to build production-ready solutions using modern ML and AI methodologies. You'll work closely with peers, product, and engineering, and play an active role in mentoring junior data scientists on the team.

What You'll Do:

• Contribute to data science projects across the full lifecycle – from problem scoping and exploratory analysis through to model development and deployment – with support from senior team members
• Develop and test Python and PySpark code on Databricks, building clean, documented, and reusable solutions for knowledge graph and identity challenges
• Apply core ML techniques – regression, classification, clustering, and model evaluation – to complex, high-volume datasets, and begin exploring advanced methods such as entity resolution, embedding-based matching, and semantic similarity
• Support MLOps practices including experiment tracking, pipeline orchestration, and model monitoring, adopting DataOps and reproducibility standards throughout
• Break down project requirements into well-scoped tasks with clear acceptance criteria, and contribute to technical documentation covering problem statements, approaches, and metrics
• Collaborate cross-functionally with product, engineering, and operations – translating business requirements into technical tasks and participating in design reviews and working groups

Who You Are:

• Bachelor's degree required in Statistics, Data Science, Computer Science, Mathematics or a related quantitative field; Master's strongly preferred
• 1 to 2 years of hands‑on data science experience with demonstrated ability to own and deliver complex, multi‑sprint projects independently
• Python with production-quality code, testing, and documentation; strong SQL and PySpark for billion-row datasets
• Databricks workflows, Delta Lake, and job orchestration; working knowledge of cloud platforms (AWS or GCP)
• Solid command of core ML – regression, classification, clustering, model evaluation, and experimental design – applied to complex, high-volume data
• Proficiency with MLOps practices: experiment tracking, pipeline orchestration (Airflow), and reproducible model deployment
• Exposure to modern AI methodologies: RAG systems, LLM-augmented models, vector databases, and semantic search
• Strong communicator – able to translate technical work into clear documentation, user stories, and cross‑functional conversations

Preferred skills:

• Hands‑on experience with knowledge graph construction, entity resolution, or semantic data modeling (RDF, OWL, SPARQL, or equivalent graph frameworks)
• Familiarity with probabilistic record linkage, identity graph approaches, or embedding-based entity matching at scale
• Experience with causal inference methods (A/B testing, synthetic control, uplift modeling)
• Experience with deduplication, enrichment, or web-to‑TV linkage problems
• Background in media, ad tech, or measurement – TV viewership (ACR/STB data), digital audience modeling, cross-platform measurement (linear + CTV/OTT), or identity resolution in privacy‑constrained environments
• Familiarity with the measurement and identity vendor landscape (Nielsen, Comscore, LiveRamp, The Trade Desk

Samba TV is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.

Samba TV may collect personal information directly from you, as a job applicant, Samba TV may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU, Samba Inc. is the data controller.