Senior Data Scientist

Overview

Senior Data Scientist to deliver hands-on advanced analytics and predictive modeling on large, complex healthcare claims datasets, supporting customer engagements and building scalable data solutions.

What you'll do

• Lead and contribute to custom projects focused on claims-based reporting, Patient Journeys, Market Assessment and predictive modeling using SQL/Python.
• Perform advanced data wrangling, transformation, and analysis on complex healthcare datasets, primarily in the claims domain.
• Create data-driven deliverables and visualizations to support customer engagements and business decision-making.
• Partner with Product and Customer Success teams to deliver insightful, tailored analyses to clients.
• Collaborate with global and cross-functional teams to design and implement optimized data solutions.
• Develop scalable tools such as solution workbenches and automated reporting systems.
• Scope, prioritize, and independently handle client requests with minimal supervision.
• Leverage SQL, Python, and Generative AI tools to drive efficiency, innovation, and automation in analytics workflows.
• Contribute to internal initiatives, knowledge sharing, and continuous improvement of team processes.
• Mentor and guide junior analysts, promoting best practices in coding, modeling, and data handling.
• Comply with information security policies and processes.
• Report security weaknesses, events or potential events, or other security risks, to the organization.
• Execute all tasks related to information security management system as appropriate.

What you'll need

• Bachelors or Masters degree in computer science, Statistics, Data Science, or a related quantitative field.
• 3–5 years of hands-on experience in data science or analytics roles, with a strong focus on SQL and Python.
• Proven expertise in healthcare data, particularly claims analytics; familiarity with pharma datasets is mandatory.
• Strong programming skills in Python, including data manipulation, wrangling, and analysis using libraries such as pandas, NumPy, and scikit-learn.
• Advanced proficiency in SQL for working with large, complex relational datasets.
• Comfortable working with large-scale data and able to assess existing processes to identify opportunities for improvement.
• Sound knowledge of statistics, data modeling, and predictive analytics.
• Proficient in Microsoft Excel and experience creating clear, impactful presentations of analytical findings.
• Strong interpersonal, communication, and presentation skills, with the ability to explain technical concepts to non-technical stakeholders.
• Self-starter with the ability to work independently and collaboratively in a fast-paced, dynamic environment.

Nice to have

• Experience or interest in Generative AI tools to enhance analytics workflows.