Senior Data Scientist

Digital Turbine • New York, NY

9d • Hybrid

About The Position

Digital Turbine is seeking a Senior Data Scientist to join their team. This role involves partnering with engineering, product, and business leaders to drive analysis that shapes strategy, including bidding efficacy, audience curation, measurement, attribution, and the centralized experimentation platform. The goal is to help build a culture of continuous, evidence-based improvement across all product surfaces by leveraging the company's extensive marketplace data. The Senior Data Scientist will frame ambiguous business problems into testable data and modeling questions, design and analyze experiments, build statistical and ML models, develop time-series and real-time event understanding, partner with engineering to productionize models, and communicate findings to both technical and executive audiences. Mentoring other analysts and scientists is also a key part of the role.

Requirements

• 8+ years in data science or quantitative analysis, ideally in AdTech, marketplaces, or consumer-scale products.
• Strong foundations in experimental design, hypothesis testing, causal inference, and statistical/ML modeling (regression, classification, clustering, time-series).
• Fluency in SQL and Python (or R), and comfort working with large-scale data in cloud data warehouses / lakes.
• Distinctive problem-solving skills and the ability to translate analysis into business recommendations.
• Excellent written and verbal communication, including the ability to influence senior stakeholders.

Nice To Haves

• Experience with Databricks, Spark, or semantic-layer / metrics platforms.
• Background in bidding, auctions, recommendation, or measurement/attribution.
• Experience standing up experimentation tooling or analytics infrastructure.

Responsibilities

• Frame ambiguous business problems as crisp, testable data and modeling questions, and deliver analysis that informs product and commercial strategy.
• Design and analyze experiments (A/B and beyond) and help establish DT's centralized experimentation tracking — a single source of truth for hypotheses, results, and decisions.
• Build statistical and ML models for audience segmentation, bid/UA optimization, lifetime value, and measurement/attribution.
• Develop time-series and real-time event understanding that improves the timeliness and relevance of recommendations and bidding.
• Partner with ML and Data Engineering to productionize models and feed insights into the Next Best Action framework.
• Communicate findings clearly to technical and executive audiences, and mentor other analysts and scientists.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed