Data Scientist

Quick Facts

• Role: Data Scientist (experienced)

• Focus: Predictive modeling and measurable impact

Description

The role owns the full lifecycle of data science projects, from exploratory analysis through building and deploying models in production. You will design and deploy predictive models to improve decision-making across service staffing optimization, marketing attribution, demand forecasting, and client retention.

Principal Duties And Responsibilities

• Design, build, and deploy predictive models to improve decision-making (service staffing optimization, marketing attribution, demand forecasting, client retention)
• Analyze complex datasets to identify patterns and generate insights supporting business strategy
• Partner with business stakeholders to frame problems, prioritize use cases, and measure impact of data science initiatives
• Work closely with data engineering to shape data infrastructure and pipelines for scalable model development
• Create compelling visualizations and reports for technical and non-technical audiences
• Contribute to data science best practices including model governance, code review, documentation, and reproducibility
• Stay current with trends in machine learning, AI, and data tooling; bring innovative thinking
• Follow data security and privacy policies; treat client and company data with confidentiality
• Report any security or privacy incidents promptly
• Provide technical guidance and mentorship to junior team members

Requirements

• 5+ years of experience in data science, analytics, or a related quantitative field
• Strong programming skills in Python (including Pandas and scikit-learn or similar)
• Proficiency in SQL and working with large-scale relational databases
• Experience with data visualization tools (e.g., Tableau or equivalent)
• Strong storytelling skills; ability to explain complex concepts to non-technical stakeholders
• Demonstrated experience leading end-to-end data science projects with measurable business outcomes

Preferred Qualifications

• Familiarity with cloud platforms (AWS, Azure) and distributed computing (Spark)
• Understanding of design, deployment, and testing of custom LLMs
• Experience deploying machine learning models to production environments
• Background in insurance, financial services, or other highly regulated industries
• Experience with A/B testing or causal inference methods

Benefits Summary

• High-quality voluntary health, vision, disability, life, and dental insurance programs
• 401K matching plan
• Employee stock purchase plan
• Paid holidays, vacation, and sick leave
• Corporate-sponsored programs to enhance employee physical, financial, mental, and emotional wellness
• Financial solution program