Lead Data Scientist

Posted Yesterday
Be an Early Applicant
2 Locations
In-Office
223K-272K Annually
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
Leads data science strategy across Digital Turbine’s mobile advertising marketplace. Designs experimentation frameworks, causal inference methodologies, and production machine learning models for bidding, audience segmentation, lifetime value, attribution, forecasting, and recommendations. Partners with engineering on deployment and monitoring, establishes scalable data science standards, mentors scientists, and communicates technical insights to executives. Requires extensive experience in data science or machine learning, advanced statistical expertise, cloud-scale data processing, and cross-functional technical leadership.
Summary Generated by Built In

At Digital Turbine, we make mobile advertising experiences more meaningful and rewarding for users, app publishers, and advertisers — intelligently connecting people in more ways, across more devices. We provide app publishers and advertisers with powerful ads and experiences that captivate consumers, fuel performance, and help telecoms and OEMs supercharge awareness, acquisition, and monetization. In a rapidly evolving industry, we are constantly innovating and creating better paths of discovery to connect consumers, publishers, and advertisers across the mobile ecosystem.

Please note that Digital Turbine is a hybrid work environment-only candidates local to the posting location will be considered.

DT has every ingredient of a marketplace business — advertisers, publishers, OEMs, carriers, consumers, devices, and proprietary device-level data. Our job in Data Science is to turn that raw advantage into intelligence: the insights, models, and systems that optimize the marketplace and prove the value we create.


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, high-ambiguity 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/UA optimization, dynamic audience segmentation, user lifetime value (LTV), and multi-touch attribution.
  • 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 into DT’s Next Best Action framework.
  • 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, and deep learning).
  • 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 Have:
  • Hands-on experience architecting metrics semantic layers or enterprise experimentation tools.
  • Deep domain expertise in real-time bidding (RTB) auctions, algorithmic yield management, or advanced attribution methodologies.
  • Masters or Ph.D. in a quantitative field (Statistics, Computer Science, Economics, Operations Research, or Physics).

At DT, we are committed to pay transparency and equitable compensation.


(For New York based candidates) The salary range for this position is $223,000-$272,000 based on experience, skills, and qualifications. In addition to competitive pay, we offer a comprehensive benefits package, including stock options, unlimited PTO and performance based bonus. We believe in fostering an environment where employees are valued and compensated fairly for their contributions.

About Digital Turbine:

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 the ability to supercharge awareness, acquisition and monetization — connecting our partners to more consumers, in more ways, across more devices.

The company is headquartered in Austin, Texas, with global offices in New York, Los Angeles, San Francisco, London, Berlin, Singapore, Tel Aviv, and other cities around the world, serving top agency, app developer, and advertising markets.

We are honored to have achieved numerous awards as an employer of choice, around the world, including: BuiltIn's Best Places to Work Awards in 2022, 2023 and 2024, DUNS 100 Best Places to Work in Tech for 2023 and 2024, and BDICode's 100 Best Companies to Work in 2024.

Digital Turbine is an equal opportunity employer committed to exemplifying diversity and inclusion around the world. We welcome people of different backgrounds, experiences, abilities, and perspectives. We embed diversity in our mindset, products, and teams to empower an inclusive, equitable, and culturally fluent environment. Building and continuously fostering this culture within our teams makes us better collaborators, partners, and innovators.

Digital Turbine will process the information you provide during the application process in accordance with the Digital Turbine Global Recruitment Privacy Notice.

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, experimental design, and machine learning architectures
  • Experience with regression, classification, time-series, clustering, and deep learning
  • 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 communication and cross-functional technical leadership skills
  • Hands-on experience architecting metrics semantic layers or enterprise experimentation tools
  • Deep expertise in real-time bidding auctions, algorithmic yield management, 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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