Data Scientist II

Job Summary:

The Data Scientist II is responsible for designing and validating predictive models, machine learning models, and artificial intelligence that inform and improve business processes across the organization (operational, clinical, financial, marketing, etc.).

Essential Functions:

Create, maintain, and communicate an analytical plan for each project

Mine and analyze large structured and unstructured datasets

Employ wide range of data sources to develop algorithms for predicting risk and understanding drivers, detecting outliers, etc.

• Develop visualizations that demonstrate the efficacy of developed algorithms
• Provide statistical validation and analysis of outcomes associated with clinical programs and interventions
• Collaborate with other teams to integrate with existing solutions
• Communicate results and ideas to key stakeholders
• Prepare code for operationalization of end-to-end model pipeline and deliverable for business consumption
• Perform any other job duties as requested

Education and Experience:

• 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 three (3) 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 preferred
• Healthcare experience is preferred

Competencies, Knowledge, and Skills:

• Proficient in SQL and at least one of the following programming languages: Python or R
• Preferred beginner level of 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

Working knowledge of predictive modeling and machine learning algorithms such as 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
• Familiarity with optimization techniques and artificial intelligence methods
• Ability to analyze large quantities of information and identify patterns, irregularities, and deficiencies
• 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

Licensure and Certification:

None

Working Conditions:

General office environment; may be required to sit or stand for extended periods of time