Sr Data Scientist, AI Studio

Job Title: Senior Data Scientist - AI StudioLocation: New York City, Boston, Holmdel, NJ, Bethlehem, PAAbout The CompanyWe are a leading insurance company on a transformation journey to evolve into a modern, forward-thinking organization committed to enhancing the wellbeing of our customers and their families. Our AI team spearheads a culture of intelligence and automation across the enterprise, creating business value from advanced data and AI solutions. Our collaborative team includes data scientists, engineers, analysts, and product leaders working together to deliver AI-driven products that power growth, improve risk management, and elevate customer experience.Job SummaryWe are looking for a Senior Data Scientist, AI Studio to join our AI team. The ideal candidate will be an experienced individual contributor with a strong background in production-ready AI/ML solutions, passionate about cutting-edge technology and applying new AI/ML algorithms and approaches. This role will involve developing advanced data science solutions, leveraging machine learning and artificial intelligence to drive enterprise-wide innovation across various business lines and products. You'll work in a team of Data Scientists led by a Lead Data Scientist and collaborate with cross-functional teams including Data Engineering and Business groups.Key ResponsibilitiesLead use cases and workstreams with junior data scientists: Provide technical leadership and mentoring while guiding project execution from conception to delivery.Support comprehensive use case development: Manage the full lifecycle including initial data exploration, project/sample design, data reception and processing, performing analysis and modeling, and creating final reports and presentations.Execute data wrangling, data matching, and ETL processes: Explore a variety of data sources, gain data expertise, perform summary analyses, and prepare modeling datasets using techniques including fuzzy matching and regular expression.Develop high-performing predictive models: Utilize advanced statistical and AI/ML techniques to create models and creative analyses that address business objectives and partner needs.Ensure data quality and model reliability: Identify source data and perform data quality checks both in model/solution development and in production environments.Package and deploy solutions: Collaborate with Data Engineers and MLOps teams to implement models in production, utilizing distributed computing and parallelism to ML solutions.Drive innovation and standardization: Implement new statistical or mathematical methodologies, propose innovative approaches using data mining and data visualization, and contribute to standardization of Data Science tools, processes, and best practices.Communicate insights effectively: Present information using data visualization techniques and communicate results and ideas to key decision makers throughout the organization.Maintain data accuracy: Perform regular data quality control, prepare and maintain reports, and troubleshoot data anomalies with consistent accuracy and thoroughness.Stay current on industry developments: Attend industry conferences to keep abreast of trends, challenges, and potential market opportunities.RequirementsEducation: PhD with 2+ years of experience, or Master's degree with 4+ years of experience in Statistics, Computer Science, Engineering, Applied Mathematics, or related fieldExperience: 3+ years of hands-on ML modeling and development experience with demonstrated track records in experimental design and executionsSkills: Strong programming skills in Python, solid understanding of data analysis and statistical modeling, solid background in algorithms and a range of ML models, hands-on experience with data wrangling including fuzzy matching and regular expression, distributed computing, and applying parallelism to ML solutionsTechnical Knowledge: Knowledge of a variety of machine learning techniques (clustering, decision tree, bagging/boosting, artificial neural networks, etc.) and their real-world advantages and drawbacksCommunication: Excellent communication skills and ability to work and collaborate cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on levelOther: Excellent analytical and problem-solving abilities with superb attention to detail, proven leadership in providing technical leadership and mentoring to data scientistsPreferred QualificationsExperience working in the insurance or financial services industryTrack record of deploying production-ready AI/ML solutions that generated measurable business valueExperience with MLOps practices and toolsPublications or presentations at industry conferencesExperience collaborating with multi-disciplinary teams including data engineers, business analysts, software developers, and functional business expertsBenefitsCompetitive Salary: Commensurate with experience and qualificationsHealth and Wellness: Comprehensive health insurance and wellness programsWork-Life Balance: Generous PTO, remote work options, and flexible hoursProfessional Development: Training programs, tuition reimbursement, and opportunities to attend industry conferencesAdditional Perks: Collaborative team environment, opportunity to work on cutting-edge AI/ML projects with real-world impact, and the chance to drive innovation at a transforming enterprise