Director, Data Science

Role overview A Director of Data Science position leading advanced marketing analytics at the intersection of data science, AI, and strategy. The role blends hands-on technical leadership with team management and client engagement, guiding a team that delivers measurement, modeling, and experimentation work for a roster of high-profile clients. It is a senior leadership role for someone who is equally comfortable building models, presenting to executives, and growing client relationships.

Responsibilities - Lead client engagements that combine data science, AI, and strategy, owning projects from scoping through delivery. - Apply advanced analytics, modeling, statistics, and experimentation techniques to solve complex marketing challenges. - Manage, mentor, and grow a team of analysts and data scientists while advising a broader group of quantitative survey researchers. - Foster a culture of innovation, collaboration, and continuous learning, ensuring consistently high-quality output. - Pitch new projects and grow existing client relationships by identifying opportunities for additional data-driven work. - Act as a thought leader on experimentation, machine learning, and emerging methods in marketing analytics, sharing insights with both clients and internal teams.

Requirements - Eight or more years of professional experience in quantitative research, marketing, or consulting. - At least two years of experience managing and developing people and teams. - Strong communication, narrative-building, and presentation skills, with the ability to speak to engineers and C-suite executives alike. - High-quality Python programming skills and comfort with Git and SQL, plus a working understanding of data pipelines. - Deep expertise implementing and explaining machine learning models such as linear and XGBoost regressions. - Strong grasp of statistics and probability applied to experimentation and marketing problems. - Proficiency analyzing both large datasets and smaller survey datasets, with a point of view on the role of AI. - Comfort with data engineering tasks, even though the primary focus is modeling rather than pipeline building.

Nice to have - Experience with mid- and upper-funnel marketing strategies. - Expertise in causal inference. - Background building generative AI applications or working with synthetic data.

Benefits and work setup - Base salary range of $140,000 to $170,000, plus eligibility for additional benefits. - Unlimited paid time off and 401(k) with company matching and no vesting period. - Annual bonuses, generous medical plan, and paid parental leave. - Distributed team across the United States.