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Develop and implement analytics applications and models to transform data into meaningful information. Design and develop data solutions using industry leading tools, technologies and best practices to profile data and develop efficient ingestion by sourcing data from PBM, Specialty, Retail, and/or HealthCare business. Develop advanced algorithms and statistical predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics and potential future outcomes.
Job Responsibility:
Develop and implement analytics applications and models to transform data into meaningful information
Design and develop data solutions using industry leading tools, technologies and best practices
Profile data and develop efficient ingestion by sourcing data from PBM, Specialty, Retail, and/or HealthCare business
Develop advanced algorithms and statistical predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics
Utilize data mining, data modeling, natural language processing, and machine learning to extract and manipulate data from multiple large data sources
Deliver predictive models that inform solutions for in-house teams and customer engagement
Visualize and interpret data and create reports
Manipulate data using statistical software
Compare models using statistical performance metrics
Support deployment of insights across multiple channels using analysis methods, machine learning, and statistical analyses
Requirements:
Master's degree in Computer Science, Data Science, Statistics, Mathematics, Analytics, Business Administration, or related field
2 years experience in marketing analytics, clinical trials, or health research
2 years experience in machine learning, statistical analysis, or predictive modeling
2 years experience with visualization tools including PowerBI or Tableau
2 years experience with traditional relational data warehouse technologies: Oracle, Teradata, or DB2
2 years experience designing data models and solutions for analytical and reporting use cases
2 years experience with NLP (Scikit-Learn, SpaCity, Pytorch, or Spark NLP)
2 years experience with machine learning algorithms
2 years experience with feature engineering, model tuning, distributed model training, and supervised and unsupervised learning implementation
2 years experience with machine learning operations
2 years experience with quantitative analysis techniques including clustering, regression, and pattern recognition
2 years experience developing data science products
2 years experience developing and deploying predictive models or ML systems in a cloud environment
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