Data Scientist

Position Summary: As a Data Scientist, Decision Insights, you’ll move beyond foundational analysis to drive real business impact. You’ll take ownership of exploratory data analysis (EDA) projects, work directly with business partners, and translate complex data into actionable insights that guide strategy and improve member experience. This role combines technical depth with a strong consultative focus—giving you the chance to stretch your skills, influence decisions, and see your work make a visible difference across the organization. Compensation: $45-$50/hour. Exact compensation may vary based on several factors, including skills, experience, and education. Key Responsibilities: • Lead or own EDA projects—from initial data exploration to delivery of actionable findings • Consult with business stakeholders to understand challenges, frame analytic problems, and co-create solutions • Synthesize analytic results into clear, compelling stories for technical and non-technical audiences • Present insights and contribute to discussions that drive business actions • Build and document reproducible analytic workflows and support scalable solutions • Uphold high standards for data quality, integrity, and best practices • Demonstrate curiosity and initiative in learning new analytic tools, methods, and industry trends Required Qualifications: • Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or related field • 1–3 years of industry experience in analytics, data science, or related roles (internships or advanced academic projects may count) • Proficiency in SQL and at least one programming language (e.g., Python, R) • Experience with data visualization tools (e.g., Tableau, Power BI) • Strong communication skills and demonstrated initiative • Ability to work both independently and collaboratively, translating business needs into analytic solutions Preferred Qualifications: • Experience in healthcare analytics or member experience domains • Familiarity with cloud data platforms (e.g., GCP, AWS) • Experience with Google BigQuery or similar cloud-based analytic tools • Exposure to machine learning techniques through coursework or projects • Advanced degree or relevant certifications