Senior Data Scientist - GenAI​/Python​/AWS​/SQL

Overview

When you join the team at Unum, you become part of an organization committed to helping you thrive. Benefits here are designed to support employees both professionally and personally, including a generous benefits package and career advancement opportunities.

Are you passionate about using AI and advanced analytics to solve complex, high‑visibility business problems? Do you thrive in an innovation‑driven environment where you can prototype, experiment, and shape the future of AI at scale? If so, this is the role for you. We are seeking a Senior Data Scientist to join our innovation hub—a small, agile team tackling the company’s most strategic challenges.

You’ll build POCs, develop end‑to‑end machine learning and generative AI solutions, and work directly with senior leaders across the enterprise.

• Bachelor’s in a quantitative field required (Master’s/PhD preferred)
• 6+ years of experience in data science or machine learning
• Strong Python and SQL skills
• Experience with cloud platforms (AWS preferred; Azure/GCP comparable)
• Databricks + PySpark experience is a strong plus
• Background in statistical modeling, ML algorithms, and feature engineering
• Ability to build automated analytics workflows and work with APIs
• Strong Communication Skills With Experience Influencing Senior Stakeholders
• Entrepreneurial mindset, curiosity, and comfort working in fast‑moving environments

• Education
  • Bachelor's degree in a quantitative field required
  • Master’s or PhD in a quantitative discipline preferred
• Experience
  • 6+ years of professional experience or equivalent relevant work
  • Proven track record leading end‑to‑end data science projects with measurable business impact
• Technical Expertise
  • Core Data Science Capabilities (expert in at least two, strong in others)
  • Programming & Automation:
    Python required; automation, Dev Ops practices, APIs, file I/O, and database integrations
  • Experience engineering solutions in cloud environments (AWS preferred; Azure/Google comparable)
  • Exposure to object‑oriented development and scalable architecture
  • Data Visualization: expertise across visualization tools; tailor visuals to business use cases
  • Statistics & Machine Learning: statistical inference, regression, feature selection/extraction, ML algorithms; experience leading end‑to‑end modeling projects
  • Data Engineering / ETL: strong SQL; design, debug, optimize complex queries; navigate large databases; combine internal and external data sources

• Strong communication skills, including the ability to influence senior leaders
• Project management expertise and strong business acumen (financial services experience a plus)
• Ability to manage multiple concurrent initiatives in a fast‑moving environment
• Comfortable leading engagements and representing analytics with executive leadership

• Analytical Solution Development: design, develop, and execute analytical solutions using optimization, simulation, machine learning, generative AI, and statistical modeling
• Construct predictive models to explain events, forecast behaviors, identify risk, or perform segmentation and clustering
• Apply domain expertise to ensure models are practical, interpretable, and aligned with business needs
• Evaluate alternative approaches and select appropriate modeling techniques for each use case

• Data Engineering & Preparation: integrate and transform large volumes of data from diverse sources to support analytics and experimentation
• Build modeling‑ready datasets using validation, reconciliation, feature engineering, and aggregation techniques
• Write complex SQL queries involving multi‑table joins, data exploration, and troubleshooting with minimal guidance
• Develop logical data models combining internal and external datasets; lead conversations with external data providers when needed

• Automation & Deployment: build automated analytics pipelines leveraging scripting, APIs, Dev Ops practices, and cloud platforms
• Partner with engineering and IT teams to scale solutions, automate workflows, and integrate models into business processes
• Play a lead role in operationalizing AI/ML solutions within…