Data Science Sr. Analyst (Hybrid)

Securian Financial • Saint Paul, MN

1d • Hybrid

About The Position

As an Operational Support Data Scientist at Securian Financial, you will bridge advanced analytics and day-to-day business operations by designing, deploying, monitoring, and continuously improving AI-driven solutions that support enterprise processes. This role focuses on supporting reliable, scalable, and explainable AI solutions that enhance operational efficiency, decision support, customer experience, and risk management across Digital, Marketing, Sales, and Servicing functions. You will operate at the intersection of data science, MLOps, and the business — ensuring models are maintained, enhanced, monitored, and aligned with Securian’s Enterprise Data Strategy Vision and Operating Principles.

Requirements

• Demonstrated experience developing, deploying, or supporting production AI/ML models in cloud environments.
• Strong proficiency in Python and experience with tools such as AWS SageMaker and GitHub.
• Experience building operationalized data science solutions (not just prototypes).
• Strong understanding of statistical modeling, machine learning algorithms, and model validation techniques.
• Ability to clearly explain technical concepts, model outputs, and operational trade-offs to stakeholders.
• Strong ethical judgment with a commitment to responsible and unbiased AI development.

Nice To Haves

• 2+ years of hands-on experience in data science, applied AI, or machine learning.
• Experience supporting AI solutions in operational or production environments.
• Familiarity with MLOps practices, model governance frameworks, and automation tooling.
• Experience working in regulated industries (financial services preferred).

Responsibilities

• AI Solution Development & Deployment: Work with business teams to enhance existing solutions to enhance and optimize existing AI/ML solutions. Deploy and manage solutions using cloud-native tools (e.g., AWS SageMaker).
• Operational Model Support & Optimization: Monitor model performance, data drift, and operational KPIs. Troubleshoot production issues and continuously enhance and optimize models for performance, stability, and cost efficiency. Establish measurement frameworks to quantify operational impact of deployed solutions.
• Data Engineering & Analytical Execution: Transform structured, semi-structured, and unstructured data into actionable features and insights. Perform exploratory analysis and visualization to identify operational improvement opportunities. Collaborate with engineering teams to productionize data solutions.
• Stakeholder Engagement & Explainability: Partner with cross-functional operational stakeholders to understand business workflows and translate them into AI-enabled solutions. Communicate complex AI methodologies and results clearly to technical and non-technical audiences. Ensure model transparency, explainability, fairness, and ethical AI application in alignment with enterprise governance standards.

Benefits

• Paid time off
• Leave programs (parental leave, caregiver leave for family members, bereavement and military leave)
• Nine company paid holidays
• Company-funded pension plan
• 401(k) retirement plan with company contribution up to 10 percent of eligible earnings, with a target of 5 percent
• Medical, dental and vision coverage from the first day of employment for associates and their eligible family members
• Volunteer paid time off
• Dollar-for-dollar matching gift program
• Associate Resource Groups (ARGs) focusing on Mental Wellness and Disability Pride, Young Professionals, Multicultural Network, Women and Allies Network, and Servicemember.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed