Data Scientist Principal

HealthPartners/GHI

Non-Union Exempt Position Summary

JOB CODE:

126067

POSITION TITLE:

Data Scientist, Principal

DATE CREATED:

February 1, 2023

DEPARTMENT:

Health Informatics, DataOps

REPORTS DIRECTLY TO:

DataOps Leadership

POSITION PURPOSE:

Our mission is to provide simple and affordable healthcare. HealthPartners teams use data to improve patient and member experience, improve health, and reduce the per capita cost of health care. HealthPartners data scientists are responsible for data exploration and interpretation of large data sets, feature engineering (data preparation) and machine learning modeling. Data scientists work in collaborative scrum teams with other developers, analysts, and data engineers, and may share accountabilities in order to achieve sprint goals. They utilize methods from quantitative disciplines (statistics, calculus, and combinatorics) and computer science disciplines (machine learning, DevOps), to extract knowledge from data, and deliver that knowledge as needed. As part of their role, data scientists describe situations, predict, or classify situations, and devise next-best-action models (prescriptive analytics).

ACCOUNTABILITIES:

• All team members must champion and model our values of partnership, curiosity, compassion, integrity, and excellence, and must contribute to a culture of continuous learning

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions

• Collaborate with data engineers to orchestrate, train, develop and operationalize learning models

• Act as or work alongside domain experts, business groups, data engineers and analysts to frame problems, model, clean and integrate data, and determine the best way to leverage that data in service of a goal

• Data scientists collaborate with other developers to design analytic and technology solutions that achieve measurable results at scale

• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.

• Leverage vast skillsets to participate in and support business analysis, sometimes on an ad hoc basis

• Champion and practice the scientific method, and motivate their teams to generate and test falsifiable hypotheses within their design systems

• Understand and (re)design the business mechanics that generate data

• Perform other duties as required, to meet team sprint goals

REQUIRED SKILLS/ QUALIFICATIONS:

• Bachelor’s degree in computer science, data or social science, operations research, statistics, applied mathematics, econometrics, or a related quantitative field. Alternate experience and education in equivalent areas such as economics, engineering or physics is acceptable

•  5+ years experience in statistical and data mining techniques, including multiple of the following: regression, random forest, boosting, text mining, hierarchical clustering, deep learning, neural networks, graph analysis

•  5+ years experience with Python or R and SQL

• Comprehensive project and/or product experience in applying machine learning and data science to business functions, including but not limited to call center automation, financial risk analytics, logistics, manufacturing, insurance, website & marketing analytics, quality assessment, production automation, e-commerce platforms, warehouse logistics, or a comparable domain

• Must be motivated, self-driven, curious, and creative

• Must be a skilled communicator, and demonstrate an ability to work with end users and business leaders

• Demonstrate the ability to support and complement the work of a diverse development and/or operations team

PREFERRED QUALIFICATIONS:

• Master’s degree in engineering, Mathematics, Statistics, or Computer Science

• Knowledge of health care operations

• Exposure to agile/scrum

• In-depth expertise and experience working with Microsoft Azure analytic tools, including Event Hubs, Data Factory, Data Lake, Purview, Synapse, Power Apps, Power BI

• Experience using data processing frameworks, like Sqoop, Spark, or Hive

• Experience with operationali