Lead Data Scientist
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Before you apply
LocationUnited States - Durham
Work modehybrid
Typefull-time
SeniorityLead
Experience8+ yrs
EquityIncluded
Company size501–1,000 people
PostedNov 3, 2026 · 5d ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
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
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)
Expert fluency in Python (or R), SQL, and handling petabyte-scale data within cloud infrastructure (e.g., Databricks, Spark, Snowflake, AWS/GCP)
Proven ability to look beyond individual analyses to design scalable tools, reusable metrics frameworks, and automated modeling pipelines
Exceptional communication and alignment skills, with a history of driving technical strategy across matrixed product, engineering, and business organizations
Lead the translation of complex, business challenges into multi-quarter data science roadmaps
Drive the methodology, design, and standards for DT's centralized experimentation framework
Architect and oversee the development of production-grade statistical and ML models for bid optimization, audience segmentation, recommendations, and user lifetime value (LTV)
Direct the strategy for time-series forecasting and real-time event processing
Partner with ML Infrastructure and Data Engineering leads to establish best practices for model deployment, monitoring, and integration
Proven ability to take theoretical state of the art advances and apply them to DT's engines in a strategic and scalable manner
Mentor senior and mid-level scientists, establish code and methodology standards, and foster an evidence-based culture
Translate deep technical findings into strategic narratives for executive stakeholders
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)
Skills
Python
R
SQL
Databricks
Spark
Snowflake
AWS
GCP
Benefits
Competitive compensation
Equity awards
Comprehensive benefits package
Hybrid work
Flexible work
About the company
DT (NASDAQ: APPS) is unifying the full mobile experience. Our growth platform powers the mobile ecosystem by bringing together advertisers, app developers, and device partners, to create a unique and premium value exchange, that results in a personalized and seamless mobile device experience.
At DT, we move fast, think big, and build collaboratively. We believe great ideas can come from anywhere, and we trust our teams to take ownership, challenge convention, and make an impact from day one.
Here, you’ll have the opportunity to grow your career while contributing to products and experiences used by millions around the world.
Benefits
With us, you will enjoy competitive compensation, equity awards, and a comprehensive benefits package designed to invest in your total well-being, all within a hybrid and flexible work environment.
About the role
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)
DT (NASDAQ: APPS) is a mobile growth platform that powers superior experiences and outcomes for advertisers, app developers, carriers, OEMs, and publishers worldwide.
Our technology connects brands and apps with consumers across devices, apps, and mobile environments — helping partners drive awareness, acquisition, engagement, and monetization through intelligent, integrated experiences.
Headquartered in Austin, Texas, DT operates globally across North America, EMEA, APAC, and LATAM.
Legal
DT is an equal opportunity employer committed to fostering an inclusive and diverse workplace. We welcome people of different backgrounds, experiences, abilities, and perspectives, and believe teams with different points of view build better products, ideas, and experiences.
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