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Head Machine Learning
Job Description
Job Title: Head of Machine Learning
Type: Direct Hire
Work Location: Hybrid position based in any of the following locations: Charlotte, NC, Atlanta, GA Raleigh, NC, Richmond, VA and Dalla, TX.
Job Overview:
The Head of Machine Learning will lead the design, development, and deployment of advanced ML solutions to transform insurance broking and underwriting operations. This role requires deep expertise in insurance domain analytics and Databricks-based machine learning pipelines, coupled with strong leadership skills to drive innovation, efficiency, and profitability.
The ideal candidate will oversee the full ML lifecycle — from ideation and modeling to deployment and monitoring — while collaborating closely with underwriting, actuarial, broking, and technology teams.— while ensuring governance, compliance, and performance at scale.
Essential Job Responsibilities:
Strategic Leadership
Required Skills & Experience:
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Job Requisition # 39753
A reasonable estimate of the Base Salary for this role is $155,000 - $175,000 per year. The disclosed pay range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. The compensation decisions are dependent on the facts and circumstances of each case, such as skills and experience levels.Â
Type: Direct Hire
Work Location: Hybrid position based in any of the following locations: Charlotte, NC, Atlanta, GA Raleigh, NC, Richmond, VA and Dalla, TX.
Job Overview:
The Head of Machine Learning will lead the design, development, and deployment of advanced ML solutions to transform insurance broking and underwriting operations. This role requires deep expertise in insurance domain analytics and Databricks-based machine learning pipelines, coupled with strong leadership skills to drive innovation, efficiency, and profitability.
The ideal candidate will oversee the full ML lifecycle — from ideation and modeling to deployment and monitoring — while collaborating closely with underwriting, actuarial, broking, and technology teams.— while ensuring governance, compliance, and performance at scale.
Essential Job Responsibilities:
Strategic Leadership
- Define the organization’s ML strategy for insurance broking and underwriting, aligning with business objectives.
- Partner with underwriting and broking leadership to identify high-value ML use cases (e.g., risk scoring, pricing optimization, customer segmentation, fraud detection).
- Champion data-driven decision-making across the organization.
- Design and build predictive and prescriptive models using Databricks Machine Learning (MLflow, Delta Lake, AutoML, Feature Store).
- Leverage historical policy, claims, market, and broker data to develop models for risk assessment, quote optimization, and cross-sell/up-sell strategies.
- Conduct exploratory data analysis (EDA) to identify trends, anomalies, and opportunities.
- Deploy models into production environments with robust monitoring and retraining pipelines.
- Architect scalable ML pipelines leveraging Databricks, Spark, and Delta Lake.
- Integrate external data sources (market data, credit data, weather data, etc.) into ML workflows.
- Ensure compliance with insurance regulations and data governance policies (GDPR, CCPA, Solvency II).
- Work closely with brokers, underwriters, and actuaries to embed ML insights into daily workflows.
- Collaborate with data engineering teams to ensure clean, high-quality, and accessible data.
- Present ML outputs and business impact in clear, non-technical terms for executives.
- Build and lead a multidisciplinary team of ML engineers, data scientists, and domain experts in a federated operating environment.
- Foster continuous learning in ML, AI ethics, insurance analytics, and regulatory compliance.
- Implement agile development practices for rapid iteration and delivery.
- Innovation & Continuous Improvement
- Evaluate emerging AI/ML techniques, including deep learning, NLP, and graph analytics, for insurance applications.
- Drive experimentation with real-time scoring and decision-support tools.
- Promote explainable AI (XAI) for transparency in underwriting decisions.
Required Skills & Experience:
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- Bachelor’s or Master’s in Data Science, Computer Science, Statistics, or related field (PhD preferred).
- 10+ years in data science/ML, with 5+ years in insurance analytics or underwriting technology leadership.
- Proven experience implementing ML solutions in insurance broking and underwriting contexts.
- Hands-on expertise with Databricks ML, MLflow, Spark, and Delta Lake.
- Proficiency in Python, SQL, and relevant ML libraries (scikit-learn, TensorFlow, PyTorch, etc.).
- Strong understanding of feature engineering, model validation, and performance optimization.
- Experience deploying ML models in production at scale.
- Knowledge of API integration for embedding ML outputs into broker/underwriter systems.
- Deep understanding of insurance product lines, risk models, and underwriting processes.
- Familiarity with rating engines, actuarial models, and market placement platforms.
- Awareness of insurance regulations, compliance, and ethics in AI use.
- Exceptional communication and stakeholder management abilities.
- Ability to bridge business needs and technical solutions.
- Strategic mindset with a bias toward measurable business outcomes.
Job Requisition # 39753
A reasonable estimate of the Base Salary for this role is $155,000 - $175,000 per year. The disclosed pay range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. The compensation decisions are dependent on the facts and circumstances of each case, such as skills and experience levels.Â
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