Lead Data Scientist: ML Strategy & Real-Time Optimization

Digital Turbine Media, Inc.; New York (NY); Hybrid; USD 223,000 - 272,000; Full time

Benefits offered by this job

Stock options

Unlimited PTO

Performance-based bonus

Job summary

Digital Turbine in New York is hiring a Lead Data Scientist to shape product strategy through data-driven roadmaps. You will translate complex business challenges into multi-quarter plans and lead production ML efforts across bidding, audience, and attribution.

This role requires 8+ years in data science, expertise in causal inference and ML architectures, and strong leadership to mentor teams and partner with engineering and product executives.

Qualifications

• 8+ years of progressive experience in data science and ML leadership.
• Expertise in statistical modeling, causal inference, experimental design, and ML architectures.
• Fluency in Python or R and handling large-scale data in cloud environments.
• Strong cross-functional collaboration and communication with product and leadership.

Responsibilities

• Define data science roadmaps aligned with product and business goals.
• Oversee centralized experimentation framework and causal inference standards.
• Architect production-grade models for bid/UA optimization, LTV, and attribution.
• Lead real-time data intelligence initiatives for forecasting and decisioning.
• Collaborate with ML Infrastructure and Data Engineering on deployment and monitoring.
• Mentor senior scientists and influence executive strategy.

Skills

Strategic framing

Experimentation framework

Advanced modeling

Causal inference

Time-series forecasting

Productionization

Leadership & mentoring

Education

Masters or PhD in a quantitative field

Tools

Python

SQL

Databricks

Spark

Snowflake

AWS

GCP

Job description

Digital Turbine in New York is hiring a Lead Data Scientist to shape product strategy through data-driven roadmaps. You will translate complex business challenges into multi-quarter plans and lead production ML efforts across bidding, audience, and attribution.

This role requires 8+ years in data science, expertise in causal inference and ML architectures, and strong leadership to mentor teams and partner with engineering and product executives.