Terminix is a member of the Rentokil family of companies, a global leader in Pest Control and other services. They are seeking a Sr. Manager, Data Scientist to lead a team focused on advancing marketing analytics capabilities, translating complex challenges into data-driven solutions, and driving insights 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