Data Scientist II - Gen AI/Python/AWS/SQL

Role Overview

Benefits

• Unum offers performance-based incentives, health and insurance benefits, paid time off, retirement contributions, mental health support, tuition reimbursement, and career development opportunities.

Education and Experience

• A bachelor's degree in a quantitative field is required; a master's degree is preferred.
• At least 4 years of professional experience or equivalent relevant work is required.

Technical Expertise

• Python is required, with experience in automation, DevOps practices, APIs, file I/O, and database integrations.
• Experience engineering solutions in cloud environments is expected; AWS is preferred, with Azure or Google as comparable alternatives.
• Core capabilities include data visualization, statistical inference, regression, feature selection, feature extraction, machine learning, SQL, ETL, and data exploration.
• Generative AI familiarity is a plus, while strong communication, project management, business acumen, and multitasking are important.

Analytical Solution Development

• Design and execute analytical solutions using optimization, simulation, machine learning, generative AI, and statistical modeling.
• Construct predictive models for explanation, forecasting, risk identification, segmentation, and clustering.
• Select appropriate modeling techniques and ensure models are practical, interpretable, and aligned with business needs.

Data Engineering and Preparation

• Integrate and transform large volumes of data from DB2, SQL Server, Teradata, APIs, and other sources.
• Build modeling-ready datasets using validation, reconciliation, feature engineering, and aggregation.
• Write complex SQL queries, develop logical data models, and coordinate with external data providers when needed.

Automation and Deployment

• Build automated analytics pipelines using scripting, APIs, DevOps practices, and cloud platforms.
• Partner with engineering and IT teams to scale solutions, automate workflows, and operationalize AI and machine learning in production.

Visualization and Collaboration

• Develop clear visualizations and communicate actionable insights to senior leaders and business partners.
• Coach junior data scientists, collaborate with product owners and engineers, and manage multiple projects independently.
• Conduct research and development on emerging statistical methods, machine learning advances, and generative AI tools.

Compensation

• The stated base salary range is $80,630 to $165,500; actual pay depends on skills, geographic location, and experience.