Sr. Manager, Data Scientist, Marketing Analytics

Accountabilities

• • Lead, mentor, and develop a team of 2–3 data scientists, establishing clear objectives, providing feedback, conducting performance reviews, and supporting professional development.

  • Foster a collaborative, high-performing environment while managing competing priorities across multiple data science initiatives.

  • Oversee the full lifecycle of data science projects, from ideation and prototyping through deployment, production monitoring, and optimization.

  • Review statistical and optimization models to ensure technical rigor, business relevance, data integrity, and adherence to appropriate ethical standards.

  • Partner with Marketing leadership and business stakeholders to understand strategic objectives and identify opportunities where data science can create measurable value.

  • Define and execute the marketing analytics roadmap in alignment with broader business priorities.

  • Lead the development and implementation of advanced analytical models, including attribution, customer lifetime value, segmentation, propensity, personalization, and media mix modeling.

  • Design and oversee A/B and multivariate testing frameworks to measure the impact of marketing initiatives.

  • Apply statistical modeling, machine learning, optimization techniques, and experimental design to address complex marketing challenges.

  • Ensure data collection, preparation, feature engineering, model development, validation, deployment, and monitoring are executed effectively.

  • Collaborate with data engineering teams to develop scalable data pipelines and analytical infrastructure.

  • Contribute hands-on expertise to deploying machine learning models within modern data science environments.

  • Champion emerging data science methods and technologies that can improve marketing performance and customer insights.

  • Translate complex analytical results into clear, actionable recommendations for marketing teams and senior executives.

  • Serve as a subject matter expert in data science and marketing analytics across the organization.

  • Collaborate with Marketing, Product, Sales, IT, and Data Engineering to drive cross-functional initiatives.

  • Stay current with industry trends, emerging technologies, and evolving best practices in marketing analytics and data science.

  Requirements

  • Master’s or PhD in Data Science, Operations Research, Applied Mathematics, Computer Science, or a related quantitative field.

  • 10+ years of progressive experience in data science, including at least 2–3 years leading or managing data science teams.

  • Extensive experience with machine learning, predictive analytics, optimization algorithms, and large-scale data processing.

  • Demonstrated experience working cross-functionally and influencing stakeholders at multiple organizational levels.

  • Experience with several marketing analytics applications, such as demand forecasting, customer segmentation, experimentation, predictive customer response, price optimization, marketing mix modeling, customer journey analytics, next-best-product/offer modeling, or customer elasticity analysis.

  • Expert-level proficiency in Python, including tools such as NumPy, pandas, scikit-learn, TensorFlow, or PyTorch, and/or strong proficiency in R.

  • Strong SQL skills for data extraction, transformation, and analysis.

  • Experience with big-data technologies such as Spark or Hadoop and cloud platforms such as AWS, GCP, or Azure.

  • Strong understanding of statistical inference, experimental design, and causal analysis.

  • Proven ability to build, deploy, monitor, and maintain machine learning models in production environments.

  • Experience developing scalable analytical pipelines and working with modern data science technology stacks.

  • Excellent written, verbal, presentation, and interpersonal communication skills.

  • Executive presence and ability to explain complex technical concepts clearly to both technical and non-technical audiences.

  • Strong strategic thinking, problem-solving capabilities, and business judgment.

  • Ability to manage multiple priorities while maintaining high standards for quality and delivery.

  • Willingness to collaborate across a large, geographically distributed organization.

  • Employment does not include visa sponsorship or OPT support.

  Benefits

  • Annual base salary range of $135,700–$176,400, with actual compensation potentially varying based on geographic location, skills, education, and experience.

  • Potential additional earnings through applicable incentives and performance-based compensation.

  • Full-time colleagues receive benefits beginning on their first day of employment, with no waiting period.

  • Medical, dental, and vision insurance.

  • Disability and life insurance coverage.

  • 401(k) retirement plan with company matching contributions.

  • Vacation and sick days.

  • Company-paid holidays and floating holidays.

  • Tuition reimbursement for eligible full-time employees.

  • Training and professional development programs.

  • Multiple opportunities for career growth and advancement.

  • Flexible work environment with an emphasis on health, safety, and work-life balance.

  • Opportunity to lead a specialized data science team and influence enterprise-level marketing strategy.