Senior Data Scientist - GenAI/Python/AWS/SQL

Unum•Portland, ME

About The Position

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! General Summary: 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. What You Bring 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

Requirements

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
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, DevOps 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.
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.

Nice To Haves

Familiarity with generative AI approaches is a plus.
financial services experience a plus

Responsibilities

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 (e.g., DB2, SQL Server, Teradata, APIs) 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, DevOps 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 production environments.
Visualization, Insights & Communication Develop and deliver clear, compelling visualizations (static or dynamic) tailored to various audiences.
Interpret analytical results and communicate actionable insights that influence senior leaders and key business partners.
Translate complex technical work into business‑friendly recommendations.
Leadership, Mentorship & Collaboration Coach, mentor, and develop junior data scientists; provide technical guidance and feedback.
Provide leadership on data science initiatives, ensuring outputs meet quality standards.
Work in a collaborative, innovation-focused environment with product owners, engineers, data architects, and business partners.
Manage multiple projects simultaneously, prioritizing independently and guiding less experienced team members.
Innovation & Research Stay current on emerging statistical methods, machine learning advancements, and generative AI tools.
Conduct independent R&D to prototype new approaches and explore innovative solutions for high‑visibility business problems.
Demonstrate entrepreneurial, self‑starter mindset with a strong curiosity and continuous‑learning orientation.

Benefits

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