Lead Data Scientist
Sagility Georgia Center, Vermont, United States · $141K–$147K/yr
Operations Consulting · 10,001+ employees
About the role
Collaborate with stakeholders to analyze business requirements and develop data-driven solutions for decision-making. Design and implement predictive models and machine learning algorithms to improve operational efficiency, fraud detection, and customer experience.
What they look for
Requirements
Requires a Bachelor's degree in Engineering, Data Analytics, or a related field and five years of relevant experience. Must possess three years of specialized experience in healthcare domain analytics, machine learning, and HEDIS measure computation.
Full description
Sagility combines industry-leading technology and transformation-driven BPM services with decades of healthcare domain expertise to help clients draw closer to their members. The company optimizes the entire member/patient experience through service offerings for clinical, case management, member engagement, provider solutions, payment integrity, claims cost containment, and analytics. Sagility has more than 25,000 employees across 5 countries.
DUTIES: Collaborate with business stakeholders to understand and analyze business requirements to develop solutions that will assist management with decision-making. Gather and analyze data from various disparate sources, which may include RDBMS, Web APIs or any other customized system. Organize large datasets to extract actionable insights and innovative ways to integrate datasets. Perform exploratory data analysis to analyze datasets and make broad conclusions based on initial evaluations. Evaluate various options in terms of appropriate modelling technique/algorithm and apply the best fit for the overall business and technical environment. Apply predictive modeling and machine learning to improve customer experiences, revenue generation, fraud detection, and cost saving, as well as other business benefits. Design and build meaningful data visualizations that explain model outcomes and link the findings with insights to describe business impact in an effective manner. EOE
REQTS: Must have a Bachelor’s degree or foreign equivalent in Engineering (Any), Data Analytics, or a related field plus five (5) years of experience in the position offered, as a Data Analyst, or a related position. Must have three (3) years of experience with all of the following: Functional domain experience in healthcare; Forming data-driven insights, designing and building analytical solutions, and validating model performance; Developing Machine Learning/AI models, statistical analysis, and data explorative techniques using Python, SAS, PowerBI, Oracle DB, and Excel; Bridging analytical insights to visualizations using dashboards, PowerBI, or Tableau; Structuring and building data-centric solutions; Building predictive models that improve savings and operational efficiency in Payment integrity (pre- and post-payment cycles); Researching and developing machine learning models to identify social determinants for population health management; Determining population health performance by coding and computing HEDIS measures (NCQA), while translating requirements and data-driven insights for annual NCQA certification; and Performing total cost of care assessments for aging populations and determining individuals at high risk for long term care utilization.
Job title:
Lead Data Scientist
Job Description:
EMPLOYER: Sagility LLC
TITLE: Lead Data Scientist LOCATION: Atlanta, GA, and various and unanticipated locations throughout the U.S. (Must be willing to work anywhere in the U.S. as the position may involve relocation to various and unanticipated client site locations; any relocation to be paid by employer pursuant to internal policy.)
DUTIES: Collaborate with business stakeholders to understand and analyze business requirements to develop solutions that will assist management with decision-making. Gather and analyze data from various disparate sources, which may include RDBMS, Web APIs or any other customized system. Organize large datasets to extract actionable insights and innovative ways to integrate datasets. Perform exploratory data analysis to analyze datasets and make broad conclusions based on initial evaluations. Evaluate various options in terms of appropriate modelling technique/algorithm and apply the best fit for the overall business and technical environment. Apply predictive modeling and machine learning to improve customer experiences, revenue generation, fraud detection, and cost saving, as well as other business benefits. Design and build meaningful data visualizations that explain model outcomes and link the findings with insights to describe business impact in an effective manner. EOE
REQTS: Must have a Bachelor’s degree or foreign equivalent in Engineering (Any), Data Analytics, or a related field plus five (5) years of experience in the position offered, as a Data Analyst, or a related position. Must have three (3) years of experience with all of the following: Functional domain experience in healthcare; Forming data-driven insights, designing and building analytical solutions, and validating model performance; Developing Machine Learning/AI models, statistical analysis, and data explorative techniques using Python, SAS, PowerBI, Oracle DB, and Excel; Bridging analytical insights to visualizations using dashboards, PowerBI, or Tableau; Structuring and building data-centric solutions; Building predictive models that improve savings and operational efficiency in Payment integrity (pre- and post-payment cycles); Researching and developing machine learning models to identify social determinants for population health management; Determining population health performance by coding and computing HEDIS measures (NCQA), while translating requirements and data-driven insights for annual NCQA certification; and Performing total cost of care assessments for aging populations and determining individuals at high risk for long term care utilization.
TRAVEL REQT: 10% domestic and international travel is required to various and unanticipated company and client sites. SALARY: $141,107 to $147,000 per year
HOURS: 40 hours per week, Monday-Friday
Location:
Work@Home NationWideUnited States of America
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