Data Scientist Lead

About the role

As the Lead Data Scientist, you will act as an internal business consultant to help optimize every facet of the organization. You will solve problems and answer questions—using data—for other departments to help reduce costs, reduce errors, and improve the organization for our 17 million members.

Responsibilities

• Partner with business teams to understand challenges, formulate analytical approaches, and deliver actionable insights that improve operational efficiency, customer experience, and business performance.
• Pull, curate, and analyze data from enterprise data platforms and cloud environments using SQL, Python, or similar tools.
• Apply statistical methods, hypothesis testing, causal inference, machine learning, and advanced analytics techniques to identify trends, determine root causes, evaluate business strategies, and measure outcomes.
• Work with large-scale datasets and collaborate closely with data engineers to build scalable analytical solutions.
• Perform exploratory analysis, dashboard development, predictive modeling, experimentation, causal impact studies, or machine learning solutions deployed into production environments.
• Design, develop, and maintain machine learning and predictive models that support business decision-making and operational efficiency.
• Identify opportunities to automate manual processes, streamline analytical workflows, and develop scalable solutions using machine learning, generative AI, intelligent agents, and workflow automation technologies.
• Partner with data engineers and business stakeholders to operationalize models, AI-powered applications, and automated processes, ensuring they are scalable, maintainable, and deliver measurable business value.
• Communicate findings and recommendations to technical and non-technical stakeholders using tools such as Tableau, Power BI, or other visualization platforms.
• Translate complex analytical concepts into clear business insights and influence decision-making across the organization.
• Lead projects, mentor junior data scientists, and guide cross-functional initiatives from concept through implementation.

Requirements

• Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, Engineering, Economics, or a related quantitative field.
• Minimum of 3 years of professional experience in data science, advanced analytics, business analytics, or a related field.
• Minimum of 1 year of experience leading projects, mentoring team members, or managing cross-functional initiatives.
• Advanced SQL skills with experience querying and analyzing large datasets.
• Strong programming experience in Python for data analysis, statistical modeling, and machine learning.
• Experience working with cloud platforms and modern data ecosystems, including AWS, Google Cloud Platform (GCP), Databricks, Snowflake, or similar technologies.
• Experience applying statistical techniques such as experimental design, hypothesis testing, statistical inference, regression analysis, causal inference, and impact measurement.
• Experience developing, validating, deploying, and monitoring machine learning models in production environments.
• Experience creating dashboards and visualizations using Tableau, Power BI, or comparable tools.
• Strong communication skills with the ability to explain technical concepts and analytical findings to non-technical audiences.

Preferred Qualifications

• Experience in the insurance industry, including claims, underwriting, actuary, or operational analytics.
• Experience supporting Agile teams and working in a sprint-based development environment.
• Experience with automation, agentic workflows, and AI-driven business solutions.

Schedule

This is a hybrid role. The candidate must reside within a 100-mile radius of the Costa Mesa, CA office and be available to work on-site 3 days a week on a regular basis, as well as 2–3 times per month for team meetings and collaboration days.

Benefits

• Health coverage for medical, dental, and vision.
• 401(K) savings plans with company match and pension.
• Tuition assistance.
• Floating holidays and PTO for community volunteer programs.
• Paid parental leave.
• Wellness programs.
• Employee discounts (membership, insurance, travel, entertainment, services, and more).