Description:

Optum is hiring an Associate Data Scientist for its analytics and business intelligence division in Hyderabad. Operating under the structural mentorship of senior data scientists, this early-career role centers on building and deploying data-driven machine learning models that optimize health delivery metrics and business performance. The day-to-day scope spans across the complete data lifecycle—from mining and cleaning raw unstructured datasets to executing statistical analysis, engineering training features, monitoring model performance drift, and using low-code/AI platforms to automate business logic pipelines.

Key Technologies:

Python, R, SQL, Power BI, Tableau, Databricks, Cloud Analytics Platforms (Azure / AWS)

Requirements:

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or a related quantitative technical discipline.
• 1+ years of hands-on corporate experience working inside predictive analytics, data science modeling, reporting, or business intelligence teams.
• Solid working understanding of predictive and descriptive statistical modeling, exploratory data analysis (EDA) workflows, and machine learning fundamentals.
• Core, foundational coding experience using Python or R for data manipulation alongside strong proficiency in SQL for relational database querying.
• Experience building clean, interactive reporting frameworks, metrics dashboards, and visual data stories using toolsets like Power BI or Tableau.
• Ability to design, configure, and roll out internal AI solutions utilizing modern no-code, low-code, and advanced intelligent platform components.
• Academic or corporate internship experience centered on supervised/unsupervised machine learning deployments, model governance, and data quality lifecycle monitoring.
• Practical familiarity working with cloud-based analytics engines, particularly Databricks, Microsoft Azure, or Amazon Web Services (AWS) environments.
• Exposure to clinical, pharmacy benefits, insurance claims, or health-payer data schemas.
• Foundational familiarity with prompt engineering paradigms, Generative AI applications, and modern automation toolsets.
• Exceptional logical problem-solving abilities, high attention to structural detail, an active continuous learning mindset, and the verbal and written communication skills required to articulate data findings to non-technical business partners.