Director of Data Science
New
J
JobgetherBenefits and protection insurance
Remote work is available only to employees residing more than 30 miles from Des Moines, Iowa; Charlotte, North Carolina; and Raleigh, North Carolina.Full-TimeDirector
Salary$165,000–$210,000 USD, depending on geographic location, professional experience, education, licensure requirements, and skill level.
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Job Details
- Experience
- At least 10 years of professional experience developing machine learning and predictive models; advanced education may be considered in place of experience.
- Required Skills
- Machine LearningData scienceGenerative AI
Requirements
- 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.
- Expertise in statistics, mathematics, machine learning, optimization, model development, operationalization, and scalability.
- Experience analyzing 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 to assess emerging AI and machine learning technologies and guide solutions from concept through production.
- Ability to connect data science initiatives to measurable business outcomes and guide scalable, production-ready delivery.
- Master's degree or PhD is advantageous.
- Experience developing custom generative AI or LLM solutions using APIs, custom prompts or models, MCP servers, and application integrations is advantageous.
- Knowledge of insurance, financial services, group benefits, or another highly regulated industry is advantageous.
Responsibilities
- Lead, mentor, and develop data scientists specializing in generative AI, machine learning, predictive modeling, and quantitative analytics.
- Define the team's technical strategy and evaluate emerging AI models, machine learning technologies, tools, and methodologies.
- Guide projects from problem definition and model design through validation, deployment, monitoring, and continuous improvement.
- Oversee 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 leaders to identify opportunities and translate technical capabilities into business outcomes.
- Establish standards and performance measures for model accuracy, production readiness, scalability, adoption, and sustained business impact.
- Set clear expectations and strengthen team effectiveness, accountability, collaboration, and continuous development.
- Support the team's growth and integration while maintaining technical quality and consistent delivery.
- Evaluate emerging technologies and promote solutions that can be deployed, scaled, and adopted across the enterprise.
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