Director of Data Science

Accountabilities:

The Director of Data Science will oversee the development and implementation of advanced analytical solutions while leading a high-performing team and aligning technical innovation with business priorities. Key responsibilities include:

• Lead, mentor, and develop a team of data scientists specializing in generative AI, machine learning, predictive modeling, and quantitative analytics.
• Define the team's technical strategy, evaluating emerging AI models, machine learning technologies, tools, and methodologies for relevant business applications.
• Guide projects throughout the full lifecycle, from problem definition and model design to validation, deployment, monitoring, and continuous improvement.
• Oversee the development of custom AI and data science solutions using structured and unstructured data, APIs, custom prompts and models, and application integrations.
• Partner with Product Management, Engineering, IT, business operations, and senior leadership to identify valuable opportunities and translate technical capabilities into business outcomes.
• Establish standards and performance measures for model accuracy, production readiness, scalability, adoption, and sustained business impact.
• Strengthen team effectiveness, establish clear expectations, and foster a culture of accountability, collaboration, and continuous development.
• Support the team's growth and integration while maintaining technical quality and consistent delivery.
• Promote a practical, results-oriented approach to data science, prioritizing solutions that can be deployed, scaled, and adopted across the enterprise.
• Encourage experimentation and ongoing evaluation of emerging technologies while ensuring solutions address real operational and strategic needs.

Requirements:

The ideal candidate combines deep technical expertise in data science with proven leadership capabilities and the ability to translate complex analytical methods into scalable business solutions. Required qualifications include:

• Bachelor's degree.
• At least 10 years of professional experience developing machine learning and predictive models; advanced education may be considered in place of experience.
• Demonstrated expertise in statistics, mathematics, machine learning, optimization, model development, operationalization, scalability, and analysis of large structured and unstructured datasets.
• Formal people management experience, including coaching technical talent and building a culture of commitment and accountability.
• Experience with modern programming languages, machine learning libraries, big-data technologies, and cloud platforms.
• Strong technical judgment and the ability to assess emerging AI and machine learning technologies, select appropriate approaches, and guide solutions from concept through production.
• Commitment to continuous learning, experimentation, and staying current with advances in AI, machine learning, and predictive modeling.
• Strong leadership, communication, and influencing skills, with the ability to drive change, navigate ambiguity, and collaborate across technical and business teams.
• Ability to connect data science initiatives to measurable business outcomes and guide the delivery of scalable, production-ready solutions.
• Authorization to work in the United States without requiring current or future immigration sponsorship. Sponsorship is not available for this position.

The following qualifications are considered advantageous:

• Master's degree or PhD.
• Experience developing custom generative AI or large language model (LLM) solutions using APIs, custom prompts or models, Model Context Protocol (MCP) servers, and application integrations.
• Experience in a high-growth or builder-oriented environment, particularly bringing emerging technologies into production.
• Knowledge of insurance, financial services, group benefits, or another highly regulated industry.

Benefits:

• Annual base salary:$165,000–$210,000 USD, depending on geographic location, professional experience, education, licensure requirements, and skill level.
• Eligibility to participate in a bonus program for non-sales positions.
• Flexible Time Off (FTO) for eligible salaried employees, covering vacation, personal time, and short-term illness. FTO does not accrue as a bank of days and has no fixed annual allocation.
• Pension eligibility.
• Comprehensive employee benefits designed to support physical, financial, and social well-being.
• Flexible work arrangements, including in-office, hybrid, and remote options subject to location requirements and agreement with the manager.
• Opportunities to lead innovative AI and data science initiatives and collaborate with senior business and technical leaders.
• Professional growth through continuous learning, experimentation, and exposure to emerging technologies.

Additional Employment Information

• Work arrangement:Remote work is available only to employees residing more than 30 miles from Des Moines, Iowa; Charlotte, North Carolina; and Raleigh, North Carolina. In-office and hybrid arrangements are also available, with hybrid work typically requiring at least three office days per week.
• Work authorization:Applicants requiring any form of current or future immigration sponsorship are not eligible.
• Code of ethics:Certain positions within asset management may be subject to an Investment Code of Ethics covering personal and business conduct, including personal trading activities.
• Application window:Applications are generally accepted for at least three full days following the original posting date, although the posting may remain open or be removed depending on application volume.