Data Scientist at Samba TV | AdTechTalent
Home / Jobs / Data Scientist Data Science 2 months ago On-site
Samba TV
Data Scientist
python pyspark databricks delta lake sql aws gcp airflow mlops machine learning ai rag systems llm vector databases semantic search data science dataops entity resolution probabilistic record linkage embedding-based matching causal inference a/b testing synthetic control uplift modeling media ad tech measurement audience modeling
Ready to apply?
Join Samba TV and work on a role built for experienced AdTech operators.
Full job description Mid-level Data Scientist role in Warsaw responsible for end-to-end delivery of data science projects with minimal guidance. Requires deep expertise in measurement or audience modelling and ability to build production-ready ML and AI solutions. Responsibilities include project ownership, methodology decisions, solution design, coding in Python and PySpark on Databricks, developing reusable tools, mentoring juniors, and cross-functional collaboration. Requires Bachelor's degree (Master's preferred) in quantitative field, 3-5 years experience, advanced Python, SQL, PySpark skills, knowledge of Databricks, Delta Lake, cloud platforms (AWS/GCP), core ML techniques, MLOps practices, and exposure to modern AI methods. Preferred skills include knowledge graph construction, probabilistic record linkage, causal inference, and media/ad tech experience.
What you'll do Own end-to-end delivery of significant data science projects from problem scoping to production deployment Make independently-reasoned decisions on methodology, model selection, and evaluation; document technical solutions Similar jobs
More roles worth a look Related opportunities based on specialty and working model so candidates can keep momentum.
TripleLift
New York, US • 4 months ago
$90K – $120K
data science machine learning python
TripleLift
Los Angeles, United States • 4 months ago
$290K – $350K
sales leadership programmatic CTV
TripleLift
Lead solution design; break down complex epics into user stories with clear acceptance criteria
Adopt DataOps and MLOps best practices including experiment tracking, pipeline orchestration, model monitoring, reproducibility
Build production-quality Python and PySpark code on Databricks; implement advanced ML and AI workflows
Develop and maintain reusable tools, libraries, and documentation to improve team efficiency and standards
Conduct code reviews with constructive feedback
Mentor junior data scientists on technical execution, code quality, and career development
Lead internal talks or workshops on ML topics
Collaborate cross-functionally with product, engineering, and operations; translate business requirements into technical specifications
Partner with data engineering on scalable pipeline design
Participate in cross-functional design reviews and working groups Requirements Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics or related quantitative field; Master's preferred 3–5 years of hands-on data science experience with ability to own and deliver complex projects independently Advanced Python with production-quality code, testing, and documentation Strong SQL and PySpark for billion-row datasets Experience with Databricks workflows, Delta Lake, and job orchestration Working knowledge of cloud platforms (AWS or GCP) Solid command of core ML techniques: regression, classification, clustering, model evaluation, experimental design Proficiency with MLOps practices: experiment tracking, pipeline orchestration (Airflow), reproducible model deployment Exposure to modern AI methodologies: RAG systems, LLM-augmented models, vector databases, semantic search Strong communication skills for documentation and cross-functional collaboration Demonstrated ability to mentor junior data scientists Tech stack Python PySpark Databricks Delta Lake SQL AWS GCP Airflow ML AI RAG systems LLM-augmented models vector databases semantic search RDF OWL SPARQL
Apply now Ready to take the next step in your career? Click the button below to continue to the application process.
Company
Samba TV Television remains a vibrant cultural influence and an essential source of entertainment and information worldwide. Tremendous growth in content choices, and viewing platforms that allow us to watch anything, anytime, on any screen, has actually made it harder for viewers to discover and keep up with all the great programming available. It’s also more competitive for content providers to keep your attention, and for marketers to make strong, measurable connections with their target consumers. Technology that improves the viewing experience, enables content discovery, and addresses audience fragmentation across screens will strengthen television’s business model and relevance to consumers. Data is at the center of any solution to make TV better. Samba TV's technology is built into Smart TVs and easily maps to smart phones and tablets. By recognizing what's on screen, Samba TV learns what viewers like and using machine learning algorithms, enables discovery of shows and actors in a whole new way. Likewise, our data and measurement products are transforming the way stakeholders across the media landscape are thinking about their business. Given the dramatic growth in streaming services, connected devices, time-shifting, and multi-screen viewership, our data products solve real problems and create a meaningful competitive advantage for our clients.
Industry
Technology, Information and Internet
Posted
2 months ago
Category: Data Science
New York, US • 4 months ago
product management CTV programmatic
