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

When you join the team at Unum, you become part of an organization committed to helping you thrive.

Here, we work to provide the employee benefits and service solutions that enable employees at our client companies to thrive throughout life’s moments. And this starts with ensuring that every one of our team members enjoys opportunities to succeed both professionally and personally. To enable this, we provide:

• Award‑winning culture
• Inclusion and diversity as a priority
• Performance Based Incentive Plans
• Competitive benefits package that includes Health, Vision, Dental, Short & Long‑Term Disability
• Generous PTO (including paid time to volunteer!)
• Up to 9.5% 401(k) employer contribution
• Mental health support
• Career advancement opportunities
• Student loan repayment options
• Tuition reimbursement
• Flexible work environments

* All the benefits listed above are subject to the terms of their individual Plans.

And that’s just the beginning…

With 10,000 employees helping more than 39 million people worldwide, every role at Unum is meaningful and impacts the lives of our customers. Whether you’re directly supporting a growing family, or developing online tools to help navigate a difficult loss, customers are counting on the combined talents of our entire team. Help us help others, and join Team Unum today!

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 or Principal 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

• Bachelor's degree in a quantitative field required.
• Master’s or PhD in a quantitative discipline preferred.

• 6+ years of professional experience or equivalent relevant work.
• Proven track record leading end‑to‑end data science projects with measurable business impact.

• Programming & Automation
• Python required; experience with 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 multiple visualization tools and techniques.
• Ability to tailor visuals to business use cases and audiences.
• Statistics & Machine Learning
• Deep knowledge of statistical inference, regression, feature selection, feature extraction, and ML algorithms.
• Experience leading large‑scale modeling projects end‑to‑end.
• Familiarity with generative AI approaches is a plus.
• Data Engineering / ETL
• Strong SQL skills; ability to design, debug, and optimize complex queries.
• Ability to navigate and explore large databases independently.
• Experience combining 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.