Lead Data Scientist

Posted 5 Days Ago
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Durham, NC, USA
In-Office
Senior level
AdTech
Awarded Best Places to Work in Austin, Los Angeles, New York, San Francisco, Seattle and Washington DC by Built In!
The Role
Lead data science strategy across product, engineering, and executive teams. Design experimentation and causal inference frameworks; architect statistical and machine learning models for bidding, segmentation, recommendations, attribution, forecasting, and lifetime value. Establish scalable metrics, deployment, monitoring, and modeling practices with infrastructure and data engineering teams. Mentor data scientists, set technical standards, influence product strategy, and translate complex findings into executive recommendations.
Summary Generated by Built In

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.

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.


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.


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.

Skills Required

  • 8+ years of progressive experience in data science, quantitative analysis, or machine learning
  • Technical leadership experience in AdTech, two-sided marketplaces, or consumer-scale data platforms
  • Expertise in advanced statistical modeling, causal inference, and experimental design
  • Expertise in machine learning architectures, including regression, classification, time-series, clustering, deep learning, multi-armed bandits, and large language models
  • Expert fluency in Python or R and SQL
  • Experience handling petabyte-scale data within cloud infrastructure
  • Ability to design scalable tools, reusable metrics frameworks, and automated modeling pipelines
  • Exceptional cross-functional communication and technical strategy leadership
  • Hands-on experience architecting metrics semantic layers or enterprise experimentation tools
  • Domain expertise in real-time bidding auctions, algorithmic yield management, large-scale content recommendation engines, or advanced attribution methodologies
  • Master's or Ph.D. in Statistics, Computer Science, Economics, Operations Research, Physics, or another quantitative field

Digital Turbine Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Digital Turbine and has not been reviewed or approved by Digital Turbine.

  • Healthcare Strength — Healthcare coverage is positioned as comprehensive, spanning medical, dental, and vision alongside life and travel insurance. Fully paid short-term disability is also presented as a meaningful safety-net benefit.
  • Equity Value & Accessibility — Equity is framed as broadly accessible, with stock/equity included for employees at hire and additional grants tied to performance. This structure can materially increase total rewards for those who value ownership and participate over time.
  • Leave & Time Off Breadth — Time-off and flexibility offerings are presented as expansive, including unlimited vacation, flexible hours, and supportive leave policies. Paid parental leave is highlighted as part of a broader leave package.

Digital Turbine Insights

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The Company
HQ: Austin, TX
950 Employees
Year Founded: 1998

What We Do

Digital Turbine (NASDAQ: APPS) powers superior mobile consumer experiences and results for the world's leading telcos, advertisers, and publishers. Our end-to-end platform uniquely simplifies our partners' ability to supercharge their awareness, acquisition, and monetization — connecting them with more consumers, in more ways, across more devices. Digital Turbine is headquartered in North America, with offices around the world. For more about Digital Turbine: www.digitalturbine.com

Why Work With Us

Everyone’s empowered to “Work their Way," while global mindsets & diverse perspectives are celebrated daily. We work hard, but also take time to enjoy the journey, and have fun while doing it. Our team is down to earth and supportive, which is needed in our fast-paced mobile ad technology space.

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