Lead Data Scientist

Digital Turbine

. Translate complex, high-ambiguity business challenges into multi-quarter data science roadmaps .

Posted 10/2/2026full-timeNew York City • New York • United StatesSenior💰 $223,000 - $272,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced statistical modeling, causal inference, and machine learning architectures, with a strong focus on designing scalable tools and automated modeling pipelines. Proven ability to translate complex data science findings into strategic narratives for executive stakeholders while fostering an evidence-based culture.

Highest-signal resume keywords

Data Science LeadershipCausal Inference ExpertiseMachine Learning ArchitecturesPython Or R ProficiencyCloud Infrastructure Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingCausal InferenceExperimental DesignRegressionClassificationTime-Series AnalysisClusteringDeep LearningSQLAutomated Modeling Pipelines

Soft Skills

Exceptional CommunicationAlignment Skills

Tools & Technologies

DatabricksSparkSnowflakeAWSGCP

Industry Keywords

AdTechTwo-Sided MarketplacesConsumer-Scale Data Platforms

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformPythonSparkSQL

About the role

Key responsibilities & impact

Translate complex, high-ambiguity business challenges into multi-quarter data science roadmaps
Drive methodology, design, and standards for the centralized experimentation framework
Serve as the primary authority on causal inference, A/B testing, and hypothesis validation
Architect and oversee production-grade statistical and machine learning models for bid/UA optimization, dynamic audience segmentation, user lifetime value, and multi-touch attribution
Direct time-series forecasting and real-time event processing strategies
Partner with ML Infrastructure and Data Engineering leads on model deployment, monitoring, and integration
Mentor senior and mid-level data scientists
Establish code and methodology standards and foster an evidence-based culture
Translate technical findings into strategic narratives for executive stakeholders
Influence product strategy and commercial investments

Requirements

What you’ll need

8+ years of progressive experience in data science, quantitative analysis, or machine learning
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
Expertise in regression, classification, time-series, clustering, and deep learning
Expert fluency in Python or R and SQL
Experience handling petabyte-scale data within cloud infrastructure such as Databricks, Spark, Snowflake, AWS, or GCP
Proven ability to design scalable tools, reusable metrics frameworks, and automated modeling pipelines
Exceptional communication and alignment skills across matrixed product, engineering, and business organizations
Masters or Ph.D. in a quantitative field is nice to have, not required
Candidates must be local to the posting location

Benefits

Comp & perks

Stock options
Unlimited PTO
Performance-based bonus
Comprehensive benefits package