Sr. Manager, Data Scientist, Marketing Analytics

Terminix, a member of the Rentokil family of companies, is a global leader in Pest Control and other services. They are seeking an experienced Sr. Manager, Data Scientist to lead a team focused on enhancing marketing analytics capabilities and driving data-driven solutions to optimize campaign performance.

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
• Apply a strong understanding of statistical modeling, machine learning algorithms, and experimental design
• Oversee the end-to-end data science lifecycle, including data collection, cleaning, feature engineering, model development, validation, deployment, and monitoring
• Ensure the integrity and accuracy of data used for analysis and modeling
• Contribute to the development of scalable data pipelines and analytical infrastructure in collaboration with data engineering teams
• Hands-on experience deploying models from development through production in a modern data science stack
• Champion the use of cutting-edge data science techniques to solve challenging marketing problems
• Partner closely with marketing leadership and stakeholders to understand business objectives and identify opportunities for data science to drive impact
• Define and execute the roadmap for marketing analytics initiatives, aligning with overall business strategy
• Lead the design, development, and implementation of advanced analytical models (e.g., attribution modeling, customer lifetime value (CLTV), segmentation, propensity modeling, personalization algorithms, media mix modeling (MMM))
• Develop and implement A/B and multivariate testing frameworks and methodologies to measure the impact of marketing initiatives
• Stay abreast of industry trends and emerging technologies in data science and marketing analytics
• Collaborate effectively with cross-functional teams including Marketing, Product, Sales, IT, and Data Engineering
• Translate complex analytical findings into clear, actionable insights and recommendations for marketing teams and senior leadership
• Act as a subject matter expert in data science and marketing analytics within the organization

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, with at least 2-3 years in a leadership or management role, leading a team of data scientists
• Extensive experience with ML predictive analytics, optimization algorithms, and large-scale data processing frameworks
• Significant experience working in cross-functional teams and influencing stakeholders at all levels of the organization
• Demonstrable experience with many of the following: Demand Forecasting, Segmentation, Testing, Predictive Customer Response, Price Optimization, Marketing Mix Modeling, Customer Journey Analytics, Next Best Product/Offer, Customer Elasticity (Market Response Modeling)
• Expert 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 (e.g., Spark, Hadoop) and cloud platforms (AWS, GCP, Azure)
• Solid understanding of statistical inference, experimental design, and causal analysis
• Proven ability to build, deploy, and monitor machine learning models in production environments
• Excellent communication, presentation, and interpersonal skills, with the ability to influence stakeholders at all levels
• Strong problem-solving abilities and a strategic mindset