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 Experienc using data processing frameworks, like Sqoop, Spark, or Hive Experience with operationalizing ML workflows using specialized MLOps frameworks such as Kubeflow, MLFlow, Liminal, Seldon Core, or general task orchestration frameworks such as AirFlow, Luigi, Argo and others. This may also include MLOps tools such as Domino Data Lab, IBM, TIBCO, Superwise.AI, Arthur.AI, Modzy, ModelOp and others Experience working with Document or NoSQL datastores, particularly MongoDB Experience working with Graph datastores, using Neo4j or TigerGraph Interest and desire to contribute to emerging practices around DataOps (CI/CD, IaC, configuration management, etc.) Experience in one or more of the following commercial/open-source data discovery/analysis platforms: KNIME, RapidMiner, Alteryx, Dataiku, H2O, Microsoft AzureML, IBM Watson Studio, STATA or SPSS, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics 126067 Data Scientist_Pcpl.doc 2 We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.