01Responsibilities
Applies knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions.Buildout in-house AI/ML products with other team members, including data scientists, IT developers, and business stakeholdersDevelop NLP and other AI/ML models including LLMs, VLMs and GenAI applications to improve risk selection and pricing.Identifies and tests hypotheses, ensuring statistical significance, as part of building and developing predictive models for business application.Translates quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data.Enables the business to make clear trade-offs between and among choices, with a reasonable view into likely outcomes.Customizes analytic solutions to specific client needs.Responsible for smaller components of projects of moderate complexity.Regularly engages with the data science community and participates in cross-functional working groups.QualificationsSolid knowledge of predictive analytics techniques and statistical diagnostics of models.Advanced fluency in Python programming including model deployment. Cloud deployment experience will be a plus.Advanced knowledge of SQL and data wrangling is required.Ability to demonstrate industry experience taking problems and translating them into analytics / data science solutions is a plus.Demonstrated ability to exchange ideas and convey complex information clearly and concisely.Has a value-driven perspective with regard to understanding of work context and impact.Candidate should possess a minimum of 2-3 yrs. of corporate experience(with a degree in math, computer science or statistics) or have a masters degree in Computer science with some corporate experience in financial services
