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Lead Data Scientist; Hybrid

Job in Saint Paul, Ramsey County, Minnesota, 55199, USA
Listing for: Securian Financial Group
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Analyst
Salary/Wage Range or Industry Benchmark: 111300 - 207800 USD Yearly USD 111300.00 207800.00 YEAR
Job Description & How to Apply Below
Position: Lead Data Scientist (Hybrid)
* At Securian Financial the internal position title is Data Science Sr Con.  
*** Position Overview
** As a Lead Data Scientist at Securian Financial, you are a recognized expert and technical leader within the organization. You will apply deep analytical and machine learning expertise to solve complex enterprise problems while shaping the technical direction of data science and AI initiatives. You seek to understand first, build scalable solutions that drive strategic growth and value, and thrive in a collaborative, teamwork-oriented environment.
You will play a key role in advancing our enterprise AI and advanced analytics capabilities, influencing tooling standards, MLOps practices, and responsible AI adoption across the organization. Our company values innovation, collaboration, and excellence, and we offer a supportive and inclusive environment where diverse perspectives are encouraged and professional growth is prioritized.
** Key Responsibilities
*** Design, develop, and product ionize advanced machine learning and AI models in partnership with data engineering and software engineering teams.
* Establish and promote MLOps best practices, including experiment tracking, model versioning, reproducibility, CI/CD, and model monitoring using tools such as MLflow and DSpy.
* Lead the design and evaluation of AI and generative AI solutions, including LLM-based systems, and agent-based workflows.
* Collaborate with cross-functional team to identify, prioritize, and deliver high-impact, data-driven solutions.
* Communicate complex analytical and model-driven insights to technical and non-technical audiences through clear narratives, reports, and presentations.
* Ensure model quality, robustness, and regulatory alignment through rigorous testing, validation, and explainability techniques.
* Drive adoption of enterprise standards for data science, machine learning, and responsible AI.
* Identify opportunities for process improvements and automation using advanced analytics and AI techniques.
* Lead and mentor more junior data scientists, providing guidance and support in their professional development while working on projects.
** Preferred Qualifications
*** A Master's or PhD degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
* At least 5 years of experience in data science or a related field, with a minimum of 2 years in a project leadership role.
* Experience building and deploying production solutions
* Experience with MLOps tools and practices, including MLflow (or similar) for experiment tracking and model management.
* 2+ years of experience in Insurance, actuarial, or a related field
* Proficiency in programming languages such as Python
* Strong expertise in machine learning frameworks and libraries (e.g., Tensor Flow, PyTorch, Scikit-learn).
* Experience with cloud platforms (e.g., AWS, Azure, Google Cloud).
* Solid understanding of statistical analysis, data visualization, data wrangling techniques, NLP approaches, ML model selection.
* Solid understanding of model approaches to satisfy regulatory requirements regarding explainability/interpretability of advanced AI/ML models
* Excellent problem-solving skills and the ability to think critically and analytically.
* Strong communication and presentation skills, with the ability to convey complex concepts to non-technical audiences.
* Demonstrated ability to manage multiple projects and prioritize tasks effectively.
* A passion for continuous learning and staying current with industry trends and developments.
** Preferred Skills
*** Experience with natural language processing (NLP), LLMs, prompt engineering, and advanced ML models.
* Familiarity with modern ML debugging, evaluation, and optimization tools such as DSpy or equivalent.
* Knowledge of responsible AI practices, including bias detection, fairness assessment, and model risk management.
* Knowledge of data governance and data privacy regulations.
* Background in finance, healthcare, or other specialized industries.#LI-hybrid   This position will be in a hybrid working arrangement.  Securian Financial believes in hybrid work as an integral part of our culture. Associates get…
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