We’re a health insurance company that acts like a technology company. We’re using software, data science and telemedicine to make health insurance more affordable, easier to access and more of a delightful experience
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We are hiring an Associate Data Scientist to transform complex data into actionable insights, partnering with stakeholders to solve business challenges through statistical analysis, machine learning, and compelling data storytelling. The ideal candidate is analytical, curious, and collaborative, skilled in data analysis, visualization, and communication, and able to translate raw data into clear, impactful recommendations.
As an Associate Data Scientist, you will do the following:
Collect, clean, and preprocess structured and unstructured datasets for analysis and modeling
Build, validate, and deploy statistical and machine learning models to solve business problems
Write optimized SQL queries to extract and manipulate data from relational databases
Develop insightful dashboards and visualizations using tools such as Power BI, Tableau, or similar
Translate technical findings into clear, actionable insights for both technical and non-technical stakeholders
Collaborate with cross-functional teams (engineering, product, operations) to define data requirements and deliver analytical solutions
Continuously monitor model performance and retrain or improve algorithms as needed
Document methodologies, workflows, and data dictionaries to ensure reproducibility
Stay updated with emerging data science, AI/ML, and analytics best practices
Requirements
Bachelor's degree (or higher) in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field
Minimum 2-3 years of proven experience in data analysis, business intelligence, or data science roles
Strong SQL skills with hands-on experience querying and joining large datasets
Proficiency in Python or R for data manipulation, statistical analysis, and modeling
Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn)
Solid understanding of statistical concepts, hypothesis testing, and data modeling
Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
Experience with version control tools (e.g., Git)
Strong communication skills for technical and non-technical audiences
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