Data Scientist III
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Job Description
Data Scientist III developing predictive models and AI for CareSource’s operational, clinical, financial, and marketing analytics. Operationalizing machine-learning pipelines and mentoring junior data scientists.
Responsibilities:
- Design and validate predictive models, machine learning models, and artificial intelligence solutions that inform and improve operational, clinical, financial, and marketing business processes
- Create, maintain, and communicate analytical plans for projects
- Balance progress across multiple concurrent projects
- Present models and analyses to management
- Mentor new and developing junior Data Scientists
- Mine and analyze large structured and unstructured datasets
- Employ a wide range of data sources to develop algorithms for predicting risk, understanding risk drivers, detecting outliers, and related applications
- Develop visualizations demonstrating algorithm efficacy
- Provide statistical validation and analysis of outcomes associated with clinical programs and interventions
- Develop innovative models to differentiate CareSource as a leader in advanced healthcare analytics
- Evaluate new software and tools to advance data science capabilities
- Lead collaboration with other teams to integrate solutions
- Communicate results and ideas to key stakeholders
- Prepare code for operationalization of end-to-end model pipelines and business deliverables
- Perform other requested job duties
Requirements:
- Bachelor’s Degree in Data Science, Mathematics, Statistics, Engineering, Computer Science, other related field or equivalent years of relevant work experience is required
- Minimum of five (5) years of experience in data analysis and/or analytic programming required
- Experience with cloud services such as Azure, AWS or GCP and modern data stack such as Databricks or Snowflakes is required
- Expert knowledge of a scientific programming language such as Python or R and SQL
- Knowledge of developing reports or dashboards in Power BI or other business intelligence applications
- Ability to perform basic statistical analyses and techniques including A/B testing, general significance testing, and sampling methodologies
- Extensive knowledge of predictive modeling and machine learning algorithms, including generalized linear models, non-linear supervised learning models, clustering, decision trees, dimensionality reduction and natural language processing
- Proficient in feature engineering techniques and exploratory data analysis
- Working knowledge of optimization techniques and artificial intelligence methods
- Ability to analyze large quantities of information and identify patterns, irregularities, and deficiencies
- Proven analytic skills in solving multi-dimensional problems and experience creating reports, projections, models, and presenting to business stakeholders
- Comfortable reading academic research papers and applying them in models
- Proficient with MS Office (Excel, PowerPoint, Word, Access)
- Demonstrated critical thinking, verbal communication, presentation, and written communication skills
- Ability to work independently and within a cross-functional team environment
Benefits:
- Bonus tied to company and individual performance may be available
- Substantial and comprehensive total rewards package
- Employee total well-being support
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