Job Description
* Develop advanced statistical and machine learning models using deep knowledge of the algorithms
* Use knowledge of python and other ML tools to write reproducible pipelines while applying coding best practices such as version control and testing where appropriate.
* Have a high degree of autonomy in following areas -- generating hypothesis, designing experiments to prove/refute the hypotheses, validating methodologies, and managing various cloud data science environments
* Work collaboratively with clients, underwriters and actuaries, show ownership, and be able to deliver results on time
* Be a key contributor to both Life and P&C business-related projects in the Americas market (US/Canada) as a first priority but also on global projects
* Maintain and grow expertise in areas such as algorithmic underwriting for both life and P&C insurance, computer vision, document information retrieval, NLP, explainability/interpretability of ML, and algorithmic fairness
* Ensure models are interpretable and communicated clearly to a range of stakeholders
* Communicate findings to team and leadership - build dashboards, visualizations, slides, and write technical reports for sharing of knowledge.
* Be aware of regulatory and reputational risk when developing AI tools and suggest ways of mitigating these
* Be fully compliant with local data protection legislation
Required Skills & Experience
* ~3-5 years' experience as a data scientist with advanced knowledge of python and ML
* Advanced understanding of supervised learning, unsupervised learning, and statistical inference
* Advanced knowledge of at least two of the following packages: xgboost, pytorch, scikit-learn
* Working knowledge of sql, prior exposure to database technologies such as mysql, snowflake, redshift, databricks preferred
* Experience with gitflow, and python packaging
* Ability to adapt communication style to the level of technical expertise of the audience
* Experience with cloud computing platforms such as AWS and Microsoft Azure
* Experience with productionizing ML models and/or building data pipelines
* Insurance industry experience is preferred, but not required
* Master's degree (Ph. D. is a plus) in Science, Technology, Engineering, Mathematics, Computer Science, Actuarial or similar quantitative field
* Bachelor's degree plus ASA or similar work experience is accepted in place of a relevant Master's degree.
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.