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.