Top Tech Jobs & Startup Jobs

Provide hands-on technical support to employees and executive leadership across Windows and Mac environments. Manage help desk requests, devices, applications, office IT infrastructure, conferencing equipment, onboarding and offboarding, MDM enrollment, access, documentation, and local and global events. Support network, VPN, Wi-Fi, productivity, and security technologies while collaborating with global IT and cross-functional teams. Occasional travel to other offices may be required.

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.

Advise Digital Turbine on global privacy and data protection matters across products, engineering, partnerships, advertising operations, and commercial deals. Responsibilities include privacy-by-design guidance, data processing agreements, international data transfers, compliance programs, privacy notices, breach response, regulatory inquiries, data subject rights, and stakeholder training. The role also negotiates privacy terms, tracks evolving laws, and develops scalable privacy processes and playbooks.

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 weekly revenue and gross profit forecasting, annual operating plan development, rolling 12-month planning, and complex financial modeling for the on-device business. Partners with commercial, operations, BI, and executive teams to build business cases, validate dashboards, deliver executive reporting, analyze actuals, and translate complex financial data into strategic insights.

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.

Design and implement full-stack features from responsive front-ends to scalable back-end services and APIs for campaign management, reporting, and marketplace optimization. Own services in production (testing, observability, performance, on-call), collaborate with product stakeholders, mentor teammates, and drive system design and backend optimization for high-throughput, low-latency environments.

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.