Senior Manager, Data Scientist, Marketing Analytics Senior Manager, Data Scientist, Marketing Analytics

About the Role

Key Responsibilities

• Lead, mentor, and develop a team of 2-3 data scientists, fostering a collaborative and high-performing environment.
• Set clear goals, provide regular feedback, and conduct performance reviews for team members.
• Support the professional growth of team members through training, conferences, and challenging assignments.
• Collaborate with cross-functional teams to identify opportunities for leveraging data science to create business value.
• Manage competing priorities across multiple projects while ensuring adherence to timelines, budgets, and quality standards.
• Oversee the end-to-end lifecycle of data science projects, from ideation and prototyping to production and monitoring.
• Conduct rigorous reviews of statistical and optimization models to ensure they meet business needs, technical standards, and ethical guidelines.
• Communicate complex analytical findings effectively at all organizational levels.
• Develop and oversee statistical modeling, machine learning algorithms, and experimental design.
• Ensure data integrity and contribute to scalable data pipelines and analytical infrastructure.
• Deploy models from development through production and monitor their performance.
• Partner with marketing leadership to understand business objectives and define analytics roadmaps.
• Design and implement advanced analytical models such as attribution modeling, CLTV, segmentation, propensity modeling, and MMM.
• Develop and execute A/B and multivariate testing frameworks to measure marketing impact.
• Translate analytical insights into actionable recommendations for marketing and senior leadership.
• Stay informed of industry trends and emerging technologies in data science and marketing analytics.
• Collaborate with teams including Marketing, Product, Sales, IT, and Data Engineering.

Requirements

• Master's or PhD in Data Science, Operations Research, Applied Mathematics, Computer Science, or a related field.
• 10+ years of progressive experience in data science, including at least 2-3 years in a leadership or management role leading data scientists.
• Extensive experience with machine learning predictive analytics, optimization algorithms, and large-scale data processing frameworks.
• Proficiency in Python (NumPy, pandas, scikit-learn, TensorFlow/PyTorch) and/or R.
• Strong SQL skills for data extraction and manipulation.
• Experience with big data technologies such as Spark and Hadoop, and cloud platforms like AWS, GCP, or Azure.
• Solid understanding of statistical inference, experimental design, and causal analysis.
• Proven ability to deploy and monitor machine learning models in production environments.
• Excellent communication, presentation, and interpersonal skills to influence stakeholders at all levels.
• Strong problem-solving skills and a strategic mindset.

Nice to Have

• Experience with demand forecasting, customer segmentation, testing, predictive customer response, price optimization, customer journey analytics, and related marketing models.
• Experience influencing cross-functional teams and stakeholders at all organizational levels.

Qualifications

• Educational background with a Master's or PhD in relevant fields.

Benefits & Perks

• Competitive base pay ranging from $135,700 to $176,400, with variations based on location, skills, and experience.
• Performance incentives, overtime, and bonuses may apply.
• Comprehensive health benefits including Medical, Dental, Vision, Disability, and Life Insurance.
• Retirement plan with company-matching contributions (401(k)).
• Paid vacation, sick days, holidays, and floating holidays.
• Opportunities for professional and personal growth, training, tuition reimbursement.
• Work-life balance initiatives and a flexible, health-conscious work environment.