Lead product data science initiatives covering data quality, anomaly detection, identity resolution, attribution, experimentation, causal inference, and incrementality measurement. Partner with product managers and platform engineers to establish reliable metrics, analytical frameworks, and measurable KPIs. Develop SQL queries and Python or R prototypes for statistical solutions and metric pipelines, while communicating methodological trade-offs to technical and business stakeholders.
Smadex is a performance advertising engine for mobile apps, enabling the world's leading marketers to grow across Mobile and Connected TV (CTV). Powered by cutting-edge data architecture and predictive analytics trained on real campaign outcomes, Smadex delivers profitable growth at scale. Headquartered in Barcelona, with teams across the Americas, EMEA, and APAC, Smadex is a business unit of Entravision (NYSE: EVC).
About the RoleWe are looking for a Senior Data Scientist to lead the analytics initiatives that underpin our core product and platform integrity. In this role, you will be the primary technical authority for Data Science for Product, owning the frameworks for data quality, accuracy, identity resolution, and incrementality measurement.
You will collaborate closely with Product Managers and Platform Engineers to ensure our analytical signals are accurate, our identity graphs are reliable, and our causal experiment frameworks deliver verifiable business value.
Responsibilities- Product Data Integrity: Own and standardize the methodologies for data quality, statistical anomaly detection, and accuracy across billions of daily auction events.
- Identity & Attribution: Investigate and design analytical methodologies around identity resolution, cross-environment matching, and privacy-first measurement frameworks.
- Experimentation & Incrementality: Develop, validate, and standardize frameworks for A/B testing, causal inference, and incrementality testing to prove genuine marketing lift.
- Product Partnership: Act as the dedicated Data Science counterpart for Product Managers, translating product roadmaps into rigorous analytical test beds and measurable KPIs.
- Advanced Analytics: Write clean, modular SQL queries and Python scripts to prototype statistical solutions, diagnostic frameworks, and metric pipelines before handing them off to platform engineering.
- Master’s or Bachelor’s degree in Statistics, Economics, Mathematics, Computer Science, Data Science, or a related quantitative discipline.
- 4+ years of professional experience in advanced data analytics, product analytics, or data science environments.
- Deep knowledge of applied statistics: causal inference, experiment design (A/B testing), regression analysis, and metric variance estimation.
- Advanced mastery of SQL and proficient data processing skills in Python or R (Pandas, NumPy, SciPy, Statsmodels).
- Demonstrated experience establishing data quality benchmarks, defining source-of-truth metrics, or working on identity/measurement models.
- Excellent communication skills, with an ability to justify statistical trade-offs and methodologies to product managers, engineers, and leadership.
- Prior experience in AdTech, programmatic bidding, or user identity frameworks is a strong plus, but strong product analytics experience from other data-intensive fields (e.g., e-commerce, fintech, marketplaces) is welcomed.
- Must be legally authorized to work in the United States without current or future sponsorship needs.
Please note that we do NOT provide VISA sponsorship. Candidates without a work authorization to work in the US won't be considered.What We Offer
- Be part of a leading, fast-growing, innovative company shaping the future of mobile advertising.
- Join a highly motivated and young team.
- Possibility of traveling to the Barcelona HQ for collaboration and team-building activities after your first year.
- Great compensation package tailored to the U.S. market.
- Medical, dental, and vision benefits plans.
- Exposure to leading global app publishers and media partners in the digital advertising industry.
- Learning and training opportunities to grow your career.
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Machine Learning • Analytics • Biotech • Generative AI
Develop and validate clinical heuristics and algorithms using real-world healthcare data. Build Python profiling pipelines, automated data-quality checks, and longitudinal patient cohorts. Analyze complex clinical databases and ETL pipelines, evaluate AI, NLP, and heuristic outputs, and collaborate with clinical, labeling, engineering, and data science teams. Maintain documentation, configuration, metrics, and validation standards for transparent, high-quality clinical analytics.
Top Skills:
Clinical Data ModelsElectronic Health Records (Ehr)ETLMatplotlibPlotlyPythonRelational DatabasesSeabornSQLTableauYaml
Artificial Intelligence • Big Data • Healthtech • Machine Learning • Analytics • Biotech • Generative AI
Leads health economics and outcomes research and real-world evidence projects for pharmaceutical, biotech, academic, and other partners. Designs and analyzes pharmacoepidemiologic studies, treatment patterns, healthcare utilization, causal inference, and survival analyses. Builds reusable analytical infrastructure, collaborates with scientists, engineers, and product teams, interprets results for stakeholders, supports publications and regulatory work, and ensures compliance with data governance and applicable regulations.
Top Skills:
GitRSQL
.jpg)
Artificial Intelligence • Computer Vision • Machine Learning • Payments • Real Estate • PropTech
Leads growth marketing data science by building attribution, lifetime value, acquisition cost, retention, and predictive models. Designs and analyzes experiments, causal inference studies, and cohort analyses to optimize marketing budgets and unit economics. Partners with Growth, Product, Finance, analytics, and engineering leaders to develop data pipelines, dashboards, and actionable strategies for acquisition, retention, and profit growth.
Top Skills:
Amazon SagemakerApache AirflowAws S3DbtLightweightmmmLookerPythonPyTorchRobynScikit-LearnSnowflakeSQLTableauTensorFlow
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
