Staff Data Scientist (Insurance Risk and Pricing)

Ladders; United States; Remote; USD 169,000 - 236,000; Full time

Benefits offered by this job

Healthcare plans

Life insurance

Disability benefits

401(k) matching

Wellbeing program

Paid holidays

Parental leave

Job summary

Ladders is seeking a Staff Data Scientist (Insurance Risk and Pricing) to join a leader in the Enterprise Technology space. This role will shape pricing and risk modeling strategy with a strong emphasis on insurance-focused analytics that improve underwriting decisions and profitability.

You will partner with cross-functional leaders to translate advanced analytics into practical business outcomes. The position requires technical leadership, mentoring, and the development of robust modeling and

Qualifications

• 10+ years of experience in data science, especially in insurance pricing or risk modeling.
• Proven technical leadership skills, including guiding complex projects and mentoring fellow data scientists.
• Experience developing, validating, and deploying GLM-based pricing models.
• Proficiency in Python and SQL, with GLMs, GBMs, and libraries like scikit-learn.
• Experience with experimental design, including A/B testing in high-traffic environments.
• Familiarity with cloud-based data platforms like BigQuery and MLOps practices.
• Master's or PhD in a quantitative field; actuarial science background is a plus.

Responsibilities

• Set the strategic vision for pricing and risk modeling and establish best practices.
• Mentor and provide technical guidance to junior data scientists.
• Design and implement GLM-based models for homeowners insurance pricing.
• Build advanced machine learning models to enhance underwriting and profitability.
• Create ensemble models to predict profitability and customer retention metrics.
• Leverage non-traditional data sources to inform localized risk assessments.
• Collaborate with cross-functional leaders to integrate data insights into business functions.
• Champion robust deployment practices and lead experimentation with emerging techniques.

Skills

Data science leadership

GLM-based pricing

Python & SQL

A/B testing

Cloud platforms (BigQuery)

MLOps practices

Insurance pricing / risk modeling

Education

Master's or PhD in a quantitative field

Actuarial science background

Tools

BigQuery

scikit-learn

MLOps

Job description

For our client, we are seeking a Staff Data Scientist (Insurance Risk and Pricing) to join the team of a leader in the Enterprise Technology space.

This role will shape the strategy for pricing and risk modeling, with a strong emphasis on insurance-focused data science work that improves underwriting decisions and profitability.

You will partner closely with cross-functional leaders to translate advanced analytics into practical business outcomes. The position also calls for technical leadership, mentoring, and the development of robust modeling and experimentation practices across the team.

Location: Remote

Compensation: $168,800 – $236,300 annually

Responsibilities

• Set the strategic vision for pricing and risk modeling and establish best practices
• Mentor and provide technical guidance to junior data scientists
• Design and implement GLM-based models for homeowners insurance pricing
• Build advanced machine learning models to enhance underwriting and profitability
• Create ensemble models to predict profitability and customer retention metrics
• Leverage non-traditional data sources to inform localized risk assessments
• Collaborate with cross-functional leaders to integrate data insights into business functions
• Champion robust deployment practices and lead experimentation with emerging techniques

Qualifications

• 10+ years of experience in data science, especially in insurance pricing or risk modeling
• Proven technical leadership skills, including guiding complex projects and mentoring fellow data scientists
• Demonstrated ability to develop, validate, and deploy GLM-based pricing models
• Proficiency in Python and SQL, particularly with implementing GLMs, GBMs, and libraries like scikit-learn
• Experience in experimental design, including A/B testing in high-traffic environments
• Familiarity with cloud-based data platforms like BigQuery and MLOps practices
• Master's or PhD in a quantitative field preferred; actuarial science background is a plus

Benefits

• Comprehensive healthcare options including medical, dental, and vision plans
• Voluntary plans for critical illness, hospital indemnity, and accidents
• Pre-tax savings options including partially employer-funded Health Savings Accounts
• Company-paid life insurance, short and long-term disability benefits
• 401(k) plans with discretionary employer matching contributions
• Employer-paid wellbeing program with access to mental health resources
• Annual wellness programs including flexible vacation, paid holidays, and parental leave

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.