The posting
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director of Data Science based in the United States.
The Director of Data Science will lead a highly technical Decision Science team focused on generative AI, machine learning, predictive modeling, and advanced analytics within the benefits and protection insurance sector. This leadership role combines technical strategy, people development, and hands-on innovation to turn emerging technologies into scalable, production-ready solutions. You will define the team's technical direction, guide complex projects from initial concept through deployment, and ensure that data science initiatives deliver measurable business value. Working closely with Product Management, Engineering, IT, and senior business leaders, you will identify high-impact opportunities and translate advanced analytical capabilities into practical solutions. You will also strengthen team performance during a period of growth and integration while fostering a culture of accountability, experimentation, and continuous learning. This is an opportunity to influence enterprise-wide innovation within an established financial services organization with a long-standing commitment to improving financial security.
Accountabilities:
- 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.
- 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.
- 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.
- 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.
- 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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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