Director of Data Science – Engineering

🔥 1 hour ago

⛰️ Colorado, Illinois, +1 more states – Remote

⛰️ Colorado – Remote 🌽 Illinois – Remote 🤠 Texas – Remote

💵 $160k - $200k / year

⏰ Full Time

🔴 Lead

📊 Data Scientist

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AdAction

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2013

📣 Marketing

💼 Consulting

📦 Logistics

Marketing • Consulting • Logistics

AdAction is a performance-driven adtech company that provides a Loyalty & Monetization Platform and a User Acquisition Engine to help brands and app platforms acquire, engage, and retain high-intent users. Its Value-Exchange Media infrastructure (including products like Qualume™, OfferIQ™, and Activate™) matches users with reward-driven offers and unifies campaign delivery, insights, and optimization to drive in-app engagement, retention, and monetization at scale. AdAction serves mobile-first marketers and publishers across industries, delivering measurable outcomes such as lower CPI, higher retention, increased offer redemptions, and improved ROAS.

📋 Description

• Lead AdAction’s Data function across Machine Learning, Data Science, Analytics, and Data Engineering • Set technical direction and develop the Data organization • Directly manage, coach, and develop ML Engineers, Data Analysts, and Data Engineers • Shape hiring, develop technical leaders and qualified reviewers, and delegate decisions • Set ML and data strategy with Technology leadership, Product, and business stakeholders • Evaluate opportunities such as conversion quality, fraud detection, personalization, forecasting, and campaign optimization • Establish baselines and success measures, track impact, and adjust initiatives • Write Python and SQL, build and evaluate models, and contribute to production implementations • Use AI-assisted coding and analysis while maintaining rigor, security, and data privacy • Pair on difficult problems and produce tested, documented work • Improve scientific thinking through problem framing, hypotheses, experiment design, statistical reasoning, model evaluation, and metric design • Coach analysts and Product Managers on measurement plans and evidence-based decisions • Establish standards for data quality, reproducibility, testing, documentation, deployment, and ongoing evaluation • Ensure models and datasets have monitoring, maintenance, and operational ownership • Lead data architecture, modeling, pipelines, and shared datasets • Partner with Engineering, Platform, and Mission Aligned Team leads on infrastructure, production integration, security, and cost • Coordinate cross-team data investments and capacity • Build reusable capabilities and shared practices while preserving local ownership

🎯 Requirements

• Typically 8+ years of relevant professional experience in Data Science, Machine Learning, or related engineering roles • Substantial hands-on experience delivering applied ML or Data Science solutions • Progressively broader technical or team leadership responsibilities • Deep applied Machine Learning and Data Science experience • Demonstrated leadership of technical practitioners through people management or senior technical leadership • Current, hands-on proficiency in Python and SQL • Demonstrated use of AI-assisted tools in day-to-day technical work • Strong statistical reasoning and analytics experience, including metric design, hypothesis testing, experiment design, and responsible interpretation of results • Credible Data Engineering knowledge across data modeling, pipelines, warehouses, and data quality • Experience with reproducibility, version control, automated testing, deployment, monitoring, and maintaining data and ML solutions after launch • Product-oriented judgment and experience prioritizing technical investments against customer and business outcomes • Ability to align multiple teams, navigate dependencies, and balance implementation with people and functional leadership • Proven ability to teach complex concepts and collaborate with technical and nontechnical colleagues in a distributed environment • Preferred: experience in advertising technology, performance marketing, fraud detection, recommendations, personalization, forecasting, or optimization • Preferred: experience with Amazon Redshift, dbt, Airflow, MLflow, Amazon SageMaker, or comparable tools • Preferred: experience leading multiple data disciplines in a smaller organization or supporting specialists embedded in cross-functional product teams • Preferred: experience with real-time or streaming analytics and event-driven data pipelines • Preferred: experience designing or evolving data architectures supporting analytics and ML • Preferred: prior direct people-management experience

🏖️ Benefits

• Fully remote work arrangement • Autonomous work environment • Growth opportunities personally and professionally • Inclusive and collaborative culture

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