As a Lead Data Scientist, you will serve as a technical authority and strategic partner across engineering, product, and executive leadership. You will define technical roadmaps, architect high-impact ML and experimentation frameworks, and set the standard for data science excellence across DT's global marketplace - from bidding efficacy and audience curation to measurement, attribution, and enterprise experimentation.
About the Lead Data Scientist role:- Strategic Problem Framing & Vision: Lead the translation of complex, business challenges into multi-quarter data science roadmaps that directly shape product strategy and commercial outcomes
- Experimentation Architecture: Drive the methodology, design, and standards for DT's centralized experimentation framework - serving as the primary authority on causal inference, A/B testing, and hypothesis validation across product surfaces
- Advanced Modeling & System Architecture: Architect and oversee the development of production-grade statistical and ML models for bid optimization, audience segmentation, recommendations, and user lifetime value (LTV)
- Real-Time Data Intelligence: Direct the strategy for time-series forecasting and real-time event processing to enhance automated decisioning, yield optimization, and recommendation engines
- Engineering Partnership & Productionization: Partner with ML Infrastructure and Data Engineering leads to establish best practices for model deployment, monitoring, and integration
- Practical Application: Proven ability to take theoretical state of the art advances and apply them to DT's engines in a strategic and scalable manner
- Technical Leadership & Mentorship: Elevate the technical rigor of the data science organization. Mentor senior and mid-level scientists, establish code and methodology standards, and foster an evidence-based culture across the company
- Executive Influence: Translate deep technical findings into strategic narratives for executive stakeholders, influencing product strategy and commercial investments
About You As the Lead Data Scientist:- Experience: 8+ years of progressive experience in data science, quantitative analysis, or machine learning, with a track record of technical leadership in AdTech, two-sided marketplaces, or consumer-scale data platforms
- Technical Mastery: Expertise in advanced statistical modeling, causal inference, experimental design, and machine learning architectures (regression, classification, time-series, clustering, deep learning, multi-armed bandits, and large language models)
- Stack & Scale: Expert fluency in Python (or R), SQL, and handling petabyte-scale data within cloud infrastructure (e.g., Databricks, Spark, Snowflake, AWS/GCP)
- Systemic Thinking: Proven ability to look beyond individual analyses to design scalable tools, reusable metrics frameworks, and automated modeling pipelines
- Cross-Functional Leadership: Exceptional communication and alignment skills, with a history of driving technical strategy across matrixed product, engineering, and business organizations
Nice to Haves:- Hands-on experience architecting metrics semantic layers or enterprise experimentation tools
- Deep domain expertise in real-time bidding (RTB) auctions, algorithmic yield management, large scale content recommendation engines, or advanced attribution methodologies
- Masters or Ph.D. in a quantitative field (Statistics, Computer Science, Economics, Operations Research, or Physics)
Headquartered in Austin, Texas, DT operates globally across North America, EMEA, APAC, and LATAM.
