Director, Data Science
Lead the research and development of marketing science and measurement capabilities at a fast-growing B2B SaaS company in the marketing analytics space. Drives scientific direction while leading and mentoring a data science team.
The Director, Data Science leads the research and development of the platform's marketing science and measurement capabilities. This role drives the scientific direction of the platform while partnering closely with Product, Engineering, and Customer teams to translate advanced analytics into scalable SaaS solutions. The role also leads and mentors a team of data scientists to ensure strong research output, technical excellence, and successful product delivery. Every team member is equipped with best-in-class technology to fuel extraordinary outcomes. Team members are expected to continuously evolve alongside these tools, using AI as a partner for momentum and innovation, raising the bar on everything built. People own the final voice, judgment, and accountability behind every deliverable.
Key responsibilities
- Lead development of advanced marketing science methodologies including causal inference, media mix modeling, marketing optimization, and experimentation.
- Oversee analytical design and evolution of the company's core measurement and optimization solutions.
- Translate scientific research and modeling results into product requirements for implementation within the SaaS platform.
- Lead and mentor a team of data scientists and analysts, ensuring high standards in research, modeling, and implementation.
- Partner with Product and Engineering teams to guide product roadmap, feature development, and technical documentation.
- Evaluate emerging technologies and research to strengthen the company's marketing measurement and optimization capabilities.
- Serve as a subject matter expert in marketing science for internal teams, customers, and business development initiatives.
What success looks like
- Advances measurement and experimentation capabilities through innovative modeling, causal inference, and analytical approaches.
- Translates advanced research into scalable product features that improve the platform and deliver measurable customer impact.
- Builds strong cross-functional partnerships with Product and Engineering to deliver high-quality data science solutions.
- Develops and mentors a high-performing data science team while maintaining strong scientific rigor and execution.
- Strengthens the company's leadership and industry reputation in marketing science and measurement.
- Evaluates and applies modern AI technologies including Generative AI, LLMs, and agentic frameworks (LangGraph, CrewAI) to improve analytics workflows, modeling productivity, and product innovation.
Ideal experience
- Education and Experience: PhD preferred in a quantitative field such as engineering, mathematics, statistics, computer science, operations research, or econometrics. 12+ years of experience developing and leading marketing analytics SaaS solutions, including MMM, optimization, A/B testing, experimentation, and customer lifetime value modeling for Retail (including D2C), CPG, and B2B clients.
- Technical and Analytical Expertise: Strong practical knowledge of marketing science, statistical modeling, and mathematical optimization. Experience with tools such as SAS, R, Python, and Gurobi, and techniques including experimental design, discrete choice models, clustering, constrained regression, smoothing and forecasting, simulation, linear programming, mixed-integer programming, and nonlinear optimization. Proficiency in scientific programming languages such as Python, R, C/C++, C#, AMPL, or MATLAB.
- Research and Product Development: Experience developing advanced statistical, machine learning, and optimization models and translating marketing science research into scalable analytical solutions and software product requirements.
- Consulting and Communication: Experience working in consultative environments delivering marketing analytics solutions. Ability to interpret complex model outputs and translate them into actionable insights and strategic recommendations. Excellent communication, writing, and presentation skills for both technical and business audiences.
- Leadership and Collaboration: Proven experience leading teams of data scientists and technical researchers with advanced quantitative degrees. Strong ability to work cross-functionally with product managers, software engineers, data modelers, and UX teams.
- Professional Growth and Industry Awareness: Self-motivated with a strong commitment to continuously expanding domain expertise, staying current with developments in marketing science, AI/ML, and statistical modeling.
- AI and Emerging Technologies: Familiarity with modern AI ecosystems including Generative AI, LLMs, and agent frameworks, and their potential applications in analytics, experimentation, and marketing intelligence.
Compensation
Competitive base + equity + comprehensive benefits. 100% remote.