Data Scientist II - People Analytics & Insights

Unum Group offers a hybrid, Chattanooga based Data Scientist II role focused on People Analytics and Insights. You will apply AI and machine learning to workforce and talent analytics, partnering with HR business partners, Talent, Operations, IT, Legal, and data leaders to turn challenges into scalable data products and production ready solutions. The position carries a salary range of USD 73,300 to 150,500 per year and requires a bachelor’s degree in a quantitative field.

Benefits

• Award-winning culture
• Inclusion and diversity as a priority
• Performance based incentive plans
• Health, Vision, and Dental coverage
• Short and Long-Term Disability insurance
• Generous paid time off, including time to volunteer
• Employer contribution up to 9.5% to 401(k)
• Mental health support
• Career advancement opportunities
• Student loan repayment options
• Tuition reimbursement
• Flexible work environments
• 401(k) employer match up to 5% plus 4.5% additional employer contribution

Responsibilities

• Design, develop, and deploy AI and machine learning solutions, including applications powered by large language models, to address complex workforce and organizational challenges
• Turn unclear HR and business questions into scalable data products, predictive models, and decision-support tools
• Build and manage end-to-end data science workflows from data extraction (enterprise data warehouses) to model deployment and monitoring
• Collaborate with HR business partners, talent leaders, and executives to deliver actionable insights on internal mobility, skills, performance, and workforce planning
• Develop and operationalize advanced analytics using modern AI frameworks such as LLMs, embeddings, and RAG architectures
• Create reusable data assets, semantic layers, and metadata frameworks to boost analytics scalability and self-service
• Work with data engineering teams to optimize data pipelines, maintain data quality, and enable near real-time analytics
• Convey complex analytical findings and AI concepts clearly to non-technical stakeholders to inform strategic decisions
• Uphold responsible AI practices, including data privacy, bias mitigation, and ethical use of employee data
• Remain current with emerging AI trends and identify opportunities to adopt new technologies within the organization

Requirements

• Bachelor’s degree in a quantitative field is required; Master’s degree is preferred
• 4+ years of professional experience or equivalent relevant work experience preferred
• Core Data Science Capabilities: demonstrated proficiency in at least two areas, with competency in others:
  • Programming and process automation: experience with file I/O, database integrations, and APIs to build automated analytics pipelines; familiarity with DevOps, automation, data mining, web scraping, or object-oriented software
  • Data visualization: expertise in at least one visualization tool and working knowledge of others, including static and dynamic visuals
  • Statistics and modeling: strong foundation in statistical inference, regression, machine learning algorithms, feature selection and extraction, and end-to-end ML tasks from problem framing to deployment
  • Data extraction, transformation, and loading: advanced SQL skills for joining multiple tables/databases, sourcing data across internal and external sources, and building logical data models
  • Core business capabilities: effective communication, experience in financial services, leadership with senior management, and disciplined multi-project prioritization
  • Leadership capabilities: ability to mentor others, adapt to change, and lead proof-of-concept work when needed
• Preferred characteristics: entrepreneurial self-starter, results-oriented problem-solver, lifelong learner with curiosity

Technologies

• LLMs
• Embeddings
• RAG architectures