Lead Data Scientist responsible for building next-generation risk models at Zego, a company transforming motor insurance for good drivers.
Responsibilities
Lead the building and scaling of next-generation risk models, overseeing everything from creative feature discovery and advanced modeling to robust pipeline deployment and long-term R&D strategy
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 2 Data Scientists 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
Requirements
Bachelor’s or Master’s degree in Statistics, Mathematics, Actuarial Science, Data Science or related field
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
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
Proficient in SQL, particularly with cloud data warehouses like Snowflake
In-depth knowledge of GLMs and other machine learning algorithms
Familiarity with cloud-based data platforms (we’re on AWS) and data visualisation tools (Looker, matplotlib, seaborn)
Experience with version control systems (e.g., Git), CI/CD pipelines, and software development best practices in a data-intensive environment
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
Benefits
Market-competitive salary
Private medical insurance
Company share options
Generous holiday allowance
Annual flexible hybrid working contribution for travel or personal development
Data Scientist/Senior Data Scientist overseeing evaluation of quantitative risk management practices at Federal Reserve Bank. Engaging in reviews, analyses, and internal consulting within the organization.
Lead Data Scientist at Federal Reserve Bank of Atlanta. Conducting quantitative risk management analysis and participating in regulatory reviews of large BHCs.
Seeking a Data Scientist/Machine Learning Semi Senior to develop data - based solutions in Buenos Aires. Must have strong Python skills and experience in Machine Learning.
Data Scientist/Developer at SEB transforming complex financial data into predictive insights through data modeling and simulations. Strong Python and finance skills required in a hybrid work environment.
Senior Data Scientist leveraging computer vision and machine learning to support Quality Control at Walmart. Collaborating with engineering and business to deliver scalable data solutions.
Senior Data Scientist addressing complex ML and AI challenges at JLL. Collaborating in a hybrid environment with a focus on real estate technology in Tel Aviv.
Applied Data Scientist designing and implementing AI - driven pipelines for Binance's blockchain products. Collaborating on complex systems to enhance market understanding and trading intelligence.
Data Science Team Lead at OREDATA, leading teams to resolve data science challenges in a hybrid environment. Joining a digital transformation firm with a strong collaborative culture.
Data Scientist analyzing claims data, optimizing processes and collaborating across departments at Allianz Spain. Utilizing statistical techniques and developing predictive models for operational efficiency.