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Posted 6 months ago
Requirements and responsibilities
About the RoleAs a Senior Data Scientist at Quandri, you will help drive the evolution of our continuous learning system behind our AI and analytics work. This role will design and implement real-time learning systems that continuously evolve Quandri's insurance intelligence from every bot interaction, document processed, and customer feedback, establishing the core infrastructure for our learning flywheel. You will build feedback loop architectures and models that capture and integrate signals from broker activities and customer interactions that improve model and product accuracy, reliability and capabilities, enabling Quandri to deliver increasingly intelligent insights that surpass any individual broker's capabilities.What you’ll doConduct advanced statistical analysis, explore complex datasets to uncover business opportunities, perform market research through dataPartner with Product, Engineering, Sales, Marketing, and Leadership stakeholders to translate business questions into analytical frameworks and data-driven solutionsBuild predictive models, forecasting, impact analysis, statistical models and the systems around them, to support business decision-makingIdentify new analytical opportunities, research emerging methodologies, leverage the AI tools, and drive data science best practicesEnd-to-end ownership: Can take models from research to production and maintain themWork closely with our team of Data Engineers, ML Engineers, AI Engineers, ML Ops, Software Engineers and other Data Scientists to integrate data insights, engineering best practices and tech review to deliver production systems and analysisOwn the ML model lifecycle for your core products (Renewals, Requoting, Connect)Build the continuous learning infrastructure that feeds back into model and product improvementThe right person for this role will haveAdvanced degree (MS/PhD) in Statistics, the Sciences, Mathematics, Computer Science or related quantitative field4-7 years of experience in data science, ML engineering or data engineering roles with proven track record of driving business impact through analyticsAdvanced proficiency in Python/R, and SQL; Expertise in building feedback loop integration systems that take feedback from engineering services, product activities, and customer interactionsStrong foundation in reinforcement learning, self-supervised learning or human in the loop learningExperience translating business problems into analytical questions and communicating technical findings to non-technical stakeholdersProven ability to communicate complex ideas clearly, collaborate across teams, lead projects from concept to delivery, and inspire others through strong leadershipExperience in agile, fast moving, and high impact business environments preferredOur guiding principles: Customers at the core. Move with urgency. Be curious. Excellence in execution. Act like an owner. Fight for simplicity.Salary Range$145,000 - $200,000 a yearCompensation and Benefits: The range for base pay is $145,000-$200,000 which is dependent on level of experience, performance and choice of stock option compensationEmployee stock options based on experience levelComprehensive health benefits, including $500 Lifestyle Spending AccountFour weeks of paid vacation per yearWork anywhere in the world for 60 calendar days of the yearParental leave top-ups: 6 months for birthing parents, 8 weeks for non-birthing parents (up to $100,000 annual salary)
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