Senior Data Scientist (Level I)

About the role

Sun Life Financial is a leading provider of employee benefits in the U.S., helping Clients achieve lifetime financial security and live healthier lives. See how at https://www.youtube.com/user/SunLifeFinancialUS The company has a stated strategic focus on leveraging data and insights to enhance our Clients' experience and drive business growth. Join our talented, diverse workforce and cultivate a rewarding career. Visit us at www.sunlife.com/us to learn more. Salary Range: $97,400 - $146,100 At our company, we are committed to pay transparency and equity. The salary range for this role is competitive nationwide, and we strive to ensure that compensation is fair and equitable. Your actual base salary will be determined based on your unique skills, qualifications, experience, education, and geographic location. In addition to your base salary, this position is eligible for a discretionary annual incentive award based on your individual performance as well as the overall performance of the business. We are dedicated to creating a work environment where everyone is rewarded for their contributions. Not ready to apply yet but want to stay in touch? Join our talent community to stay connected until the time is right for you! We are committed to fostering an inclusive environment wher

Benefits

Additional Information

Sun Life U.S. is one of the largest providers of employee and government benefits, helping approximately 50 million Americans access the care and coverage they need. Through employers, industry partners and government programs, Sun Life U.S. offers a portfolio of benefits and services, including dental, vision, disability, absence management, life, supplemental health, medical stop-loss insurance, and healthcare navigation. We have more than 6,400 employees and associates in our partner dental practices and operate nationwide. Visit our website to discover how Sun Life is making life brighter for our customers, partners and communities. Job Description: This role will provide advanced analytics expertise within the Business Analytics function that applies the power of data with machine learning to improve business outcomes across the Health and Risk Solutions business. This team is expected to work closely with the other teams across the organization, including functional teams and the analytic agile squads supporting AI use cases within various business domains. This position reports to the Director of Advanced Analytics Transformation within the Health and Risk Solutions business. Responsibilities include development and monitoring of predictive model and AI solutions to support our pricing, underwriting, claim forecasting, and clinical review processes. Additional responsibilities may include applying machine learning techniques to streamline and automate aspects of these processes, mentoring junior team members, and promoting a culture of data-driven risk-based decisions. How will you contribute? Independently apply data science techniques to solve business problems across various analytical areas, including exploratory data analysis, feature engineering, predictive modeling, and visualization Develop, validate, and maintain high-quality, robust predictive models and AI solutions that meet business and technical requirements Utilize multiple sources of data, including structured and unstructured data, along with a variety of machine learning techniques to improve model performance and interpretability Write clean, modular, and well-documented code that can be deployed and maintained in production, while providing technical guidance and code reviews for junior team members. Interpret data and model outputs to generate clear actionable insights and recommendations that influence business decisions. What will be needed to succeed? Strong knowledge of statistical and machine learning framework, with a deep conceptual understanding of time series mythologies and forecasting techniques Proficiency in Python and SQL for data manipulation, modeling, and automation Strong problem-solving skills and effective communication, with an ability to explain complex technical concepts to a non-technical audience Ability to turn proof-of-concept model into production-ready code and reproducible workflows Commitment to data compliance, model governance and security protocols Strong business acumen to understand why and how the work we do will impact our business stakeholders BS/MS in a statistical, mathematical, or technical field (e.g., computer science, actuarial science) 3+ years of experience in developing and implementing data science techniques What will be nice to have? Experience with actuarial/pricing, underwriting or related concepts utilized in the health insurance field Demonstrated academic or industry experience with generative AI including prompt engineering, RAG workflows and integrating LLMs into business process Familiarity with MLOps practices, including model deployment, monitoring, and lifecycle management

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