Data Scientist

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Offered From the posting source checked Jun 20, 2026

Verification

Not verified

Salary

$120K-$150K From the posting source checked Jun 20, 2026

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

U.S. benchmark only; posted salary is not compared across countries or currencies.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Data Scientist Remote Position Summary The Data Scientist is responsible for applying advanced analytics, statistical modeling, and machine learning techniques to support strategic decision-making across the organization. This role partners closely with stakeholders in Underwriting, Actuarial, Claims, Product, Revenue, and Customer Experience to translate business questions into analytical solutions that improve operational performance, risk evaluation, and customer outcomes. The Data Scientist develops predictive models, explores new data sources, and generates actionable insights that support pricing, underwriting, claims management, and operational efficiency. This role also contributes to the development and operationalization of models and analytics solutions by working with engineering and product teams to integrate insights into business tools, dashboards, and workflows. Essential Duties and Responsibilities - Partner with stakeholders across Underwriting, Actuarial, Claims, Product, and Revenue to identify opportunities where data can inform better business decisions. - Translate business questions into analytical frameworks, hypotheses, and statistical approaches. - Analyze customer, broker, and operational data to identify trends, anomalies, and opportunities to improve engagement, retention, and operational performance. - Conduct exploratory data analysis to investigate business problems and generate actionable insights. - Communicate analytical findings through visualizations, dashboards, and written summaries. - Develop predictive models and statistical analyses to support pricing, underwriting, claims, reserving, and operational initiatives. - Apply machine learning techniques including regression, classification, clustering, and other statistical learning methods to solve complex business problems. - Evaluate model performance and continuously improve models based on new data and changing business needs. - Explore internal and third-party data sources to enhance

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