We are looking for a Senior Data Scientist to join AI team, the team behind underwriting decisions, quote-time risk scoring, and portfolio analytics.
In this role, you will own entire research directions: framing the problem, deciding what's worth measuring, designing the approach from first principles, and turning
the result into production signal. The work is production-oriented applied research on hard, real-world datasets where standard recipes don't apply and the right method
often has to be invented for the problem.
What You'll Do:
– Own open-ended research directions end-to-end – from a vague business question to a deployed, validated signal.
– Work across the team's core research areas – risk modeling, environmental and catastrophe modeling, and behavioral modeling – translating complex real-world processes
into reliable predictive signal.
– Deeply investigate existing production models – understand what they actually learn, where they break, and where the headroom is; identify and ship optimizations
grounded in that understanding.
– Design approaches from first principles when off-the-shelf methods don't fit the data.
– Build rigorous evaluations and own the result in production, not just the notebook.
– Document research clearly so findings are reproducible, auditable, and compound over time.
In this role, you will own entire research directions: framing the problem, deciding what's worth measuring, designing the approach from first principles, and turning
the result into production signal. The work is production-oriented applied research on hard, real-world datasets where standard recipes don't apply and the right method
often has to be invented for the problem.
What You'll Do:
– Own open-ended research directions end-to-end – from a vague business question to a deployed, validated signal.
– Work across the team's core research areas – risk modeling, environmental and catastrophe modeling, and behavioral modeling – translating complex real-world processes
into reliable predictive signal.
– Deeply investigate existing production models – understand what they actually learn, where they break, and where the headroom is; identify and ship optimizations
grounded in that understanding.
– Design approaches from first principles when off-the-shelf methods don't fit the data.
– Build rigorous evaluations and own the result in production, not just the notebook.
– Document research clearly so findings are reproducible, auditable, and compound over time.
Requirements:
– MSc. or PhD in Statistics, Applied Math, Physics, or a closely related quantitative field.
– Real research experience – a track record of driving original investigations end-to-end (academic research, a research-heavy PhD, industry R&D, or equivalent), not
only applied ML delivery.
– Strong mathematical or statistical problem-solving instincts – able to model a messy real-world system from scratch, not just apply a library.
– Production deployment experience: monitoring, CI/CD, data validation, reproducibility.
– Ability to independently initiate, plan, and drive entire research directions.
– Team player, positive, driven, independent, fast learner.
Advantages
– Depth in classical statistics, causal inference, or applied probability.
– Deep learning experience.
– Clean coding and repository-maintenance
– MSc. or PhD in Statistics, Applied Math, Physics, or a closely related quantitative field.
– Real research experience – a track record of driving original investigations end-to-end (academic research, a research-heavy PhD, industry R&D, or equivalent), not
only applied ML delivery.
– Strong mathematical or statistical problem-solving instincts – able to model a messy real-world system from scratch, not just apply a library.
– Production deployment experience: monitoring, CI/CD, data validation, reproducibility.
– Ability to independently initiate, plan, and drive entire research directions.
– Team player, positive, driven, independent, fast learner.
Advantages
– Depth in classical statistics, causal inference, or applied probability.
– Deep learning experience.
– Clean coding and repository-maintenance
This position is open to all candidates.





