Data Science Manager
- Establish a reliable Data Science workflow - clear guard-rails, templates, and documentation across the full project lifecycle
- Shorten the idea-to-production cycle - from first data pull to live rate change
- Foster a culture of collaborative experimentation - pairing Pricing, Data Science, Machine Learning Engineering & Systems Engineering
- Line management and mentorship - Manage around 4 Data Scientists or Analysts and mentor members of the team and help them in their development
- Define coding standards and best practice, map common processes and establish playbooks for them
- Help decide on tooling used during the Data Science project lifecycle
- Education: Bachelor's or Master's degree in Statistics, Mathematics, Actuarial Science, Data Science or related field
- Experience: At least 5 years proven experience in insurance pricing and applied ML, including leading projects and people, with a particular focus on Data Science operations
- Technical Skills:
- Python Proficiency: Strong Python programming skills, with experience in developing and maintaining analytics packages and tools. Familiarity with data science libraries such as pandas and scikit-learn
- SQL: Proficient in SQL, particularly with cloud data warehouses like Snowflake
- Statistical Methodology: In-depth knowledge of GLMs and other machine learning algorithms
- Data Tools: Familiarity with cloud-based data platforms (we're on AWS) and data visualisation tools (Looker, matplotlib, seaborn)
- Software Engineering:
- Experience with version control systems (e.g., Git), CI/CD pipelines, and software development best practices in a data-intensive environment
- Ability to balance architecture thinking with heads-down coding
- Soft Skills:
- Excellent communication and project management skills, with a proven ability to work collaboratively across teams and present complex information in a clear, accessible way
- Care about documentation, reproducibility, and teaching others "the why" behind decisions
- Exposure to telematics or usage-based insurance data
- Experience designing or maintaining MLOps platforms
- Hands-on experience with insurance pricing tools like Akur8, Emblem or similar pricing modelling tools
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