[Hiring] Data Scientist - Modeling @Mercury Insurance Services

Role Description

This individual contributor position is responsible for supporting analytical projects on identifying business opportunities, answering business questions, and developing business solutions. The team member will need to be able to understand business needs and create research and implementation plans using data, statistical models, and machine learning techniques. The team member needs to have strong data and programming skills and be able to work closely with cross-functional teams of software engineers, data analysts, and product leaders on business initiatives.

Responsibilities

• Work with various business departments to understand business processes and needs.
• Identify the right business sources related to issues and opportunities.
• Conduct project work as assigned and perform ad-hoc analyses using statistical and machine learning algorithms.
• Work independently with guidance from advanced level data scientists and management.
• Participate in discussions regarding analysis needs and review analyses with colleagues and managers.
• Provide data support on projects and work closely with business on implementation.
• Create monitoring procedures and reports for projects implemented.
• Understand data sources from different applications and data infrastructure.
• Retrieve large amounts of structured or unstructured data and apply advanced data manipulation techniques.
• Review data for accuracy and optimize methods of data retrieval.
• Create, maintain, and improve dynamic reports, graphs, and charts.
• Create procedures to streamline analysis procedures.
• Establish automated procedures to reduce costs and improve efficiency.
• Answer questions and conduct ad hoc analysis from business on related reports.
• Communicate proactively with SMEs, EBI, IT, and Management.
• Create presentations breaking down problems identified and potential solutions.
• Actively participate in meetings to present findings and recommendations.
• Regular attendance at work on a full-time schedule of at least 8 hours and 40 hours per week.
• Other functions may be assigned.

Qualifications

• Minimum: Bachelor’s degree in math, statistics, computer science, or other related areas.
• Preferred: Master’s Degree (or ACAS/FCAS).
• Minimum: At least 2 years of experience in data mining and data/statistical analysis.
• Minimum: At least 2 years experience with SQL and statistical software packages (Python, R, SAS).
• Minimum: At least 1 year experience working as a data scientist or similar role.
• Minimum: At least 1 year of experience in insurance or financial service related fields.
• Preferred: Experience building and delivering a survival or churn model.
• Preferred: Experience building refreshable model or analytical pipelines.
• Preferred: Experience with model orchestration tools (e.g., Metaflow, Airflow).

Requirements

• Demonstrated solid skills in data mining, machine learning, programming, and optimization.
• Knowledge with cloud-based advanced data and analytics environment.
• Passion for problem-solving and comfort with ambiguity.
• Ability to think conceptually, analytically, and creatively.
• Experience using R, Python, and other programming languages.
• Strong data skills and the ability to work with large structured and unstructured data sources.
• Experience in predictive modeling, general model building, and validation procedures.
• Excellent problem-solving skills required.
• Excellent analytical and critical thinking required.
• Excellent written and verbal communication skills required.
• Demonstrate Company’s Core Values.

Benefits

• Competitive compensation.
• Flexibility to work from anywhere in the United States for most positions.
• Paid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours).
• Incentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus).
• Medical, dental, vision, life, and pet insurance.
• 401 (k) retirement savings plan with company match.
• Engaging work environment.
• Promotional opportunities.
• Education assistance.
• Professional and personal development opportunities.
• Company recognition program.
• Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions.