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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.
Job Responsibility:
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
Requirements:
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)