Sr Data Scientist

Northwestern Mutual • Milwaukee, WI

1d • $118,960 - $178,440

About The Position

As part of the AI organization, the Sr Data Scientist works with a collaborative team to solve complex problems and turn new ideas into meaningful outcomes. The role applies advanced statistical, mathematical, data-mining, predictive-modeling, and business-analysis methods to discover insights, predict and prescribe outcomes, identify actionable opportunities, and measure results.

The position develops LLM-based and other mathematical models, algorithms, machine-learning techniques, and analytics for insights and visualization of complex datasets, supporting productization and monetization. It creates evaluation frameworks and monitors deployed models and AI systems for performance, drift, and unintended outcomes. The role also accesses and extracts data from diverse platforms and sources, builds complex data models and information solutions, and collaborates across the enterprise to meet data needs. The Senior Data Scientist shares practices and mentors peers while working with internal and external teams to deliver projects.

The listed compensation range is $118,960–$178,440, with geographic-specific ranges of $130,880–$196,320 for Structure 110 and $136,800–$205,200 for Structure 115. Final compensation depends on factors including candidate skills and experience, market, and location.

Requirements

• At least 5 years of relevant experience with demonstrated success using data science to deliver significant business impact or develop data- or algorithm-based products.
• Proficiency in Python and SQL.
• Experience with common machine-learning libraries, such as scikit-learn, and cloud data platforms, such as Databricks.
• Experience designing agents and multi-agent workflows, including tool integration, orchestration, guardrails, and human-in-the-loop checkpoints.
• Understanding of context engineering, including how to structure instructions, retrieved information, tool outputs, and memory so AI systems perform reliably.
• Understanding of AI system evaluation, including accuracy, hallucination rates, consistency, and cost/latency, using structured test sets and human review.
• Ability and desire to mentor team members through projects independently from start to finish and work with internal and external teams.
• Excellent time- and project-management skills, including managing detailed work and communicating project status effectively to all levels.
• Proven track record of meeting aggressive deadlines.
• Bachelor’s degree in Data Science, Statistics, Mathematics, Operations Research, Computer Science, Econometrics, or a related quantitative field.
• Skills in applying cloud architecture principles across AWS and Azure; industry knowledge; Python or R for coding, statistical analysis, and graphics; statistical analysis; MLOps; and machine learning.

Nice To Haves

• A Master’s or PhD in a related quantitative field.

Responsibilities

• Apply advanced statistical, mathematical, data-mining, predictive-modeling, and business-analysis techniques to discover insights, predict and prescribe outcomes, identify actionable opportunities, and track and measure results.
• Develop LLM-based and other mathematical models, algorithms, machine-learning techniques, and analytics to support insights and visualization of complex datasets for productization and monetization.
• Create evaluation frameworks and monitor deployed models and AI systems for performance, drift, and unintended outcomes.
• Use creative problem solving and cross-departmental networking to address enterprise data and information needs.
• Coach and mentor peers in core methodologies, patterns, standards, and processes; guide team members through projects from start to finish.
• Access and extract data from diverse sources on multiple platforms, and implement complex data models and information solutions by combining, synthesizing, and structuring data from multiple sources.
• Work with internal and external teams to make decisions and maintain project momentum.
• Manage project timelines and detailed work, communicate status effectively to all levels, and meet aggressive deadlines.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior