Jobs at Digital Turbine

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.

Lead product marketing strategy for a mobile advertising portfolio, including market research, positioning, commercialization, go-to-market operations, product launches, sales enablement, customer proof points, and lifecycle optimization. Partner cross-functionally with Product, Engineering, Sales, Partnerships, Research, and Marketing to align product strategy with customer and commercial needs. Mentor teammates and improve scalable PMM processes, frameworks, and execution quality.

Owns strategic intelligence and ecosystem monitoring across mobile, ad tech, AI, competition, regulation, and public markets. Partners with the Chief Strategy Officer and senior leaders to synthesize insights, shape corporate, product, partnership, and go-to-market strategies, and support executive decisions. Builds innovation and incubation frameworks, uses AI to prototype products, and connects successful concepts to product execution. This hands-on role requires strong cross-functional influence, technical fluency, and executive communication.

Design, build, and deploy large-scale ML systems for ad ranking, bid optimization, and recommendations. Build and operate production ML pipelines (feature engineering, distributed training, deployment, retraining, monitoring) that process billions of events and serve low-latency predictions. Optimize training and inference for compute and cost efficiency. Partner with Data Science, Data Engineering, and product teams to ship models, run online experiments, and measure CTR/CVR/ROI impact. Incorporate applied ML research and techniques into advertising and audience modeling.

Lead data science efforts to design experiments, build statistical and ML models (audience segmentation, bidding, LTV, attribution), develop time-series and real-time event understanding, productionize models with engineering, and communicate insights to inform product and commercial strategy.

Lead strategy and roadmap for on-device distribution platform and SDK consolidation. Manage and grow a product management team, own carrier/OEM and developer partnerships, drive platform security and compliance, and translate regulatory shifts into product priorities to scale global partner adoption and monetization.