Data Scientist

September 16

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healthcare payments • payment integrity • payment accuracy • healthcare bill review • electronic payments

1001 - 5000

💰 $20.1M Venture Round on 2020-01

Description

• 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. • Understand business use case requirements and develop appropriate machine learning algorithms to provide solutions to the business problems. • 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. • Develop and maintain data visualizations to communicate insights and recommendations to stakeholders. • 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. • Maintain a focused, flexible, organized, proactive and positive behavior and approach. • 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. • Developed and implemented Gen AI use cases.

Requirements

• Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related field preferred. • 3+ years of experience in data science, machine learning, or a related field. • Proficiency in programming languages such as Python, R, or Java. • Experience with statistical analysis and modeling. • Experience with data visualization tools such as Tableau or Power BI. • Experience with database technologies such as SQL, NoSQL, or MongoDB. • Strong problem-solving skills and the ability to analyze complex data sets. • Excellent communication skills and the ability to present technical concepts to non-technical stakeholders. • Gen AI experience is a must.