Rentokil is seeking an experienced Sr. Manager, Data Scientist to lead a team focused on advancing marketing analytics capabilities, translating complex marketing challenges into data-driven solutions to optimize campaign performance, enhance customer understanding, and maximize ROI.
Requirements
- 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.
- Extensive experience with ML predictive analytics, optimization algorithms, and large-scale data processing frameworks.
- 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).
Responsibilities
- Lead, mentor, and develop a team of 2-3 data scientists, fostering a collaborative and high-performing environment.
- 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.
- Contribute to the development of scalable data pipelines and analytical infrastructure in collaboration with data engineering teams.
- Champion the use of cutting-edge data science techniques to solve challenging marketing problems.
Other
- 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.
