Sr. Data Scientist

Lincoln Financial Group is seeking a Data Scientist to join our AI Product & Delivery organization, focused on the agentic AI systems powering our next generation of products. You will generate insights from data, build and validate models, design experiments, and measure the business value AI agents deliver - while establishing rigorous evaluation frameworks that keep agentic systems accurate, safe, and reliable in a regulated financial services environment. You will partner closely with product owners, engineers, and business stakeholders to turn analysis into decisions and evals into guardrails.

What you’ll be doing

Insights & Analysis

Analyze usage, performance, and outcome data to surface actionable insights on how agentic AI features are used and where they fall short. Translate findings into clear, actionable recommendations for product, engineering, and business stakeholders. Build and maintain dashboards and reporting that track agent performance and business impact.

Modeling & Agentic AI Systems

Design, build, and validate models and agentic workflows. Evaluate model and agent architecture choices, balancing accuracy, latency, cost, and risk. Collaborate with engineering to productionize models and agents and monitor them post-launch.

Experimentation

Design and run experiments - A/B tests, offline evaluations, holdouts - to test agent behavior, prompt or model changes, and feature variants. Define hypotheses, success metrics, and sample size or power requirements; ensure statistical rigor. Interpret results and translate them into clear go/no-go recommendations.

Value Measurement

Define and track metrics that connect agentic AI features to business value - efficiency gains, cost savings, revenue, and customer or employee experience. Build measurement frameworks that isolate AI-driven impact from other contributing factors. Report on ROI and value realization to product and business leadership.

Evaluations (Evals) for Agentic AI

Design and maintain eval suites and benchmarks covering task success, reasoning quality, tool-use correctness, safety, and failure modes. Build regression frameworks and test case libraries to catch performance degradation across model or prompt updates. Partner with product owners on human-in-the-loop review processes and use eval findings to guide model and agent improvements., This position may be subject to Lincoln’s Political Contribution Policy. An offer of employment may be contingent upon disclosing to Lincoln the details of certain political contributions. Lincoln may decline to extend an offer or terminate employment for this role if it determines political contributions made could have an adverse impact on Lincoln’s current or future business interests, misrepresentations were made, or for failure to fully disclose applicable political contributions and or fundraising activities.

Any unsolicited resumes or candidate profiles submitted through our web site or to personal e-mail accounts of employees of Lincoln Financial are considered property of Lincoln Financial and are not subject to payment of agency fees.

Lincoln Financial (“Lincoln” or “the Company”) is an Equal Opportunity employer and, as such, is committed in policy and practice to recruit, hire, compensate, train and promote, in all job classifications, without regard to race, color, religion, sex, age, national origin or disability. Opportunities throughout Lincoln are available to employees and applicants are evaluated on the basis of job qualifications. If you are a person with a disability that impedes your ability to express your interest for a position through our online application process, or require TTY/TDD assistance, contact us by calling (866) 922-6543.

3-8 years of experience in data science, applied machine learning, or a related analytical role. Hands-on experience building and evaluating ML models; experience with agentic AI systems (LLM agents, tool use, multi-step reasoning) strongly preferred. Experience designing and analyzing experiments (A/B testing, causal inference, or similar). Proficiency in Python, SQL, and standard ML/data science tooling. Strong ability to communicate technical findings to non-technical stakeholders. Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field. Grade level: final grade level for this position will be determined based on the selected candidate’s experience.

Nice to haves (preferred)

Experience building or evaluating LLM-based agents or multi-agent systems. Familiarity with eval frameworks and observability tools (e.g., LangSmith, Weights & Biases, Ragas). Experience with LLM APIs or enterprise AI platforms (e.g., Azure OpenAI, AWS Bedrock, Anthropic Claude, Google Vertex AI). Advanced degree (Master’s or Ph.D.) in a quantitative field. Domain experience in life insurance, annuities, retirement planning, or employee benefits. Application Deadline

3.53.5 out of 5 stars Radnor, PA Hybrid work $96,900 - $176,200 a year, Pulled from the full job description

• Tuition reimbursement
• Parental leave
• Paid time off
• Employee assistance program, Applications for this position will be accepted through August 31, 2026, subject to earlier closure due to applicant volume.

What’s it like to work here?

At Lincoln Financial, we love what we do. We make meaningful contributions each and every day to empower our customers to take charge of their lives. Working alongside dedicated and talented colleagues, we build fulfilling careers and stronger communities through a company that values our unique perspectives, insights and contributions and invests in programs that empower each of us to take charge of our own future.

What’s in it for you: Clearly defined career tracks and job levels, along with associated behaviors for each of Lincoln’s core values and leadership attributes

Leadership development and virtual training opportunities

PTO/parental leave

Competitive 401K and employee benefits

Free financial counseling, health coaching and employee assistance program

Tuition assistance program

Work arrangements that work for you

Effective productivity/technology tools and training

The pay range for this position is $96,900 - $176,200 with anticipated pay for new hires between the minimum and midpoint of the range and could vary above and below the listed range as permitted by applicable law. Pay is based on non-discriminatory factors including but not limited to work experience, education, location, licensure requirements, proficiency and qualifications required for the role. The base pay is just one component of Lincoln’s total rewards package for employees. In addition, the role may be eligible for the Annual Incentive Program, which is discretionary and based on the performance of the company, business unit and individual. Other rewards may include long-term incentives, sales incentives and Lincoln’s standard benefits package.

Lincoln Financial (NYSE: LNC) helps people to confidently plan for their version of a successful future. We focus on identifying a clear path to financial security, with products including annuities, life insurance, group protection, and retirement plan services.

With our 120-year track record of expertise and integrity, millions of customers trust our solutions and service to help put their goals in reach.

Lincoln Financial Distributors, a broker-dealer, is the wholesale distribution organization of Lincoln Financial. Lincoln Financial is the marketing name for Lincoln Financial Corporation and its affiliates including The Lincoln National Life Insurance Company, Fort Wayne, IN, and Lincoln Life & Annuity Company of New York, Syracuse, NY. Lincoln Financial affiliates, their distributors, and their respective employees, representatives and/or insurance agents do not provide tax, accounting or legal advice.

Lincoln is committed to creating an inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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