Data Scientist - Healthcare Analytics

Role: Data Scientist - Healthcare Analytics

Location: Bangalore (Hybrid)

Experience : 5 years

Qualification: Bachelors or Masters degree in computer science, Statistics, Data Science, or a related quantitative field.

Summary:

Senior Data Scientist with strong SQL/Python, data wrangling, and analytics expertise for high-impact healthcare projects. The role focuses on analyzing large complex datasets, building scalable data solutions, and generating actionable insights to support business decisions. Ideal candidates should understand business context, excel in claims analytics, apply quantitative methods effectively, and bring a proactive learning mindset.

1. Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
2. Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
3. Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
4. Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
5. Develop scalable tools such as solution workbenches and automated reporting systems.
6. Scope, prioritize, and independently handle client requests with minimal supervision.
7. Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
8. Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
9. Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.

Qualifications

1. 5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL and Python.
2. Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets is mandatory, experience in healthcare analytics.
3. Strong programming skills in Python, including data manipulation, wrangling, and analysis using libraries such as pandas, NumPy, and scikit-learn.
4. Advanced proficiency in SQL for working with large, complex relational datasets.
5. Comfortable working with large-scale data and able to assess existing processes to identify opportunities for improvement.
6. Sound knowledge of statistics, data modeling, and predictive analytics.
7. Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical findings.
8. Strong interpersonal, communication, and presentation skills, with the ability to explain technical concepts to non-technical stakeholders.