Data Scientist

About Us 

Zelis is modernizing the healthcare financial experience in the United States (U.S.) across payers, providers, and healthcare consumers. We serve more than 750 payers, including the top five national health plans, regional health plans, TPAs and millions of healthcare providers and consumers across our platform of solutions. Zelis sees across the system to identify, optimize, and solve problems holistically with technology built by healthcare experts – driving real, measurable results for clients.

Why We Do What We Do 

In the U.S., consumers, payers, and providers face significant challenges throughout the healthcare financial journey. Zelis helps streamline the process by offering solutions that improve transparency, efficiency, and communication among all parties involved. By addressing the obstacles that patients face in accessing care, navigating the intricacies of insurance claims, and the logistical challenges healthcare providers encounter with processing payments, Zelis aims to create a more seamless and effective healthcare financial system.

Zelis India plays a crucial role in this mission by supporting various initiatives that enhance the healthcare financial experience. The local team contributes to the development and implementation of innovative solutions, ensuring that technology and processes are optimized for efficiency and effectiveness. Beyond operational expertise, Zelis India cultivates a collaborative work culture, leadership development, and global exposure, creating a dynamic environment for professional growth. With hybrid work flexibility, comprehensive healthcare benefits, financial wellness programs, and cultural celebrations, we foster a holistic workplace experience. Additionally, the team plays a vital role in maintaining high standards of service delivery and contributes to Zelis’ award-winning culture. 

Position Overview

Zelis is looking for a Senior Data Scientist who will collaborate with our analytics and data engineering teams to collect, analyze, and derive insights from company, client, and publicly available data. The ideal candidate must have strong experience in data mining/data analysis/predictive modeling, using a variety of data tools, building, and implementing models, supervised and unsupervised learning, NLP, feature reduction, cluster analysis and creating/running simulations. They must be comfortable working with a wide range of stakeholders and functional teams. 

Essential Duties and Functions 

• Understand the business objective and directly participate in the delivery of data science solutions to solve business problems.
• Extract and analyze data: assessing quality, profiling, cleansing, exploratory data analysis and the transformation of large and complex datasets to be utilized for developing the statistical models.
• Design and develop different statistical modeling techniques such as regression, classification models, anomaly detection models, clustering models, deep learning models and feature reduction etc. to derive actionable insights.
• Build, test, validate models through various relevant methodologies, error metrics and calibration techniques.
• Validate the post-production model performance and calculate the ROI
• Work with cloud analytic platforms on AWS/ Azure using PySpark, Sagemaker, Snowflake, Azure Synapse Analytics, etc. 
• Perform multiple tasks and deal with changing deadline requirements. This includes knowing when to escalate issues. Maintain a focused, flexible, organized, proactive and positive behavior and approach.  
• Monitor the projects of Junior Data Scientists, and mentor and provide them guidance when needed.
• Proactively provide recommendations to the business based on the insights derived from data science modeling techniques to resolve business problems.
• Communicate data science models’ complex results and the insights to the non-technical audiences.
• Interact with cross-functional technical teams and multiple business stakeholders to support integration of data science solutions into the business processes.

Experience, Qualifications, Knowledge, and Skills 

• Advanced degree in data science, statistics, computer science, or equivalent with a background in statistics. 
• Experience with healthcare and/or insurance data is a plus.
• Proficiency in SQL, Python/R, NLP and LLM 
• 3-5 years of relevant work experience including 5 years of experience in developing algorithms using data science technologies to evaluate data scenarios and future outcomes.
• Competent in machine learning principles and techniques.
• Experience with cloud-based data and AI solutions.
• Familiarity with collaboration environments (e.g. Jupyter notebooks,gitlab ,github etc)