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Data Scientist V - Medicare, ACA, Risk Adjustment
Oakland, CA
Full-time
Hybrid
Senior Level, Lead/Staff
$174K/yr - $226K/yr
8+ years expKaiser Permanente is seeking a Data Scientist to support their Prospective Risk Adjustment Operations team. This role is responsible for leading the design and development of data pipelines, conducting complex data analysis, and partnering with stakeholders to deliver data-driven insights in a healthcare setting.
Computer Software
Responsibilities
Promotes learning in others by communicating information and providing advice to drive projects forward; builds relationships with cross-functional stakeholders. Listens, responds to, seeks, and addresses performance feedback; provides actionable feedback to others, including upward feedback to leadership and mentors junior team members. Practices self-leadership; creates and executes plans to capitalize on strengths and improve opportunity areas; influences team members within assigned team or unit. Adapts to competing demands and new responsibilities; adapts to and learns from change, challenges, and feedback. Models team collaboration within and across teams
Conducts or oversees business-specific projects by applying deep expertise in subject area; promotes adherence to all procedures and policies. Partners internally and externally to make effective business decisions; determines and carries out processes and methodologies; solves complex problems; escalates high-priority issues or risks, as appropriate; monitors progress and results. Develops work plans to meet business priorities and deadlines; coordinates and delegates resources to accomplish organizational goals. Recognizes and capitalizes on improvement opportunities; evaluates recommendations made; influences the completion of project tasks by others
Leads the development of detailed problem statements outlining hypotheses and their effect on target clients/customers by ensuring comprehensive and accurate definitions of scope, objectives, outcome statements and metrics
Leads the design and development of data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats by overseeing the transformation, cleansing, and storing of data for consumption by downstream processes; writing and optimizing diverse and complex SQL queries; and demonstrating expertise of database fundamentals
Serves as an expert in the analysis and investigation of complex data sets by ensuring optimum data visualization methods are employed; determining how best to manipulate data sources to discover patterns, spot anomalies, test hypotheses, and/or check assumptions; and reviewing and verifying summaries of key dataset characteristics
Leads the selection, manipulation, and transformation of data into features used in machine learning algorithms by leveraging and demonstrating expertise in techniques to conduct dimensionality reduction, feature importance, and feature selection
Trains statistical models by selecting and leveraging algorithms and data mining techniques; leading model testing by ensuring the proper use of various algorithms to assess the input dataset and related features; and applying techniques to prevent overfitting such as cross-validation
Leads the deployment and maintenance of reliable and efficient models through production
Verifies and ensures model performance by demonstrating advanced expertise in the practice of a variety of model validation techniques to assess and discriminate the goodness of model fit; and leveraging feedback and output to manage and strengthen model performance
Partners with internal and external stakeholders across domains to develop and deliver statistical driven outcomes by generating and delivering insights and values from heterogeneous data to investigate complex problems for multiple use cases; driving informed decision-making; and presenting findings to both technical and non-technical leadership
Qualification
Required
Minimum three (3) years experience working with Exploratory Data Analysis (EDA) and visualization methods
Minimum five (5) years machine learning and/or algorithmic experience
Minimum five (5) years statistical analysis and modeling experience
Minimum five (5) years programming experience
Minimum three (3) years experience in a leadership role with or without direct reports
Bachelors degree in Mathematics, Statistics, Computer Science, Engineering, Economics, Public Health, or related field AND Minimum eight (8) years experience in data science or a directly related field. Additional equivalent work experience in a directly related field may be substituted for the degree requirement. Advanced degrees may be substituted for the work experience requirements
Knowledge, Skills, and Abilities (KSAs): Strategic Thinking; Advanced Quantitative Data Modeling; Algorithms; Applied Data Analysis; Data Extraction; Data Visualization Tools; Deep Learning/Neural Networks; Machine Learning; Relational Database Management; Project Management; Microsoft Excel; Design Thinking; Business Intelligence Tools; Data Manipulation/Wrangling; Data Ensemble Techniques; Feature Analysis/Engineering; Open Source Languages & Tools; Model Optimization; Data Architecture; Data Engineering
Preferred
One (1) year healthcare experience
One (1) year regulatory experience
Company
Jobs via Dice
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Funding
Current Stage
Early StageCompany data provided by crunchbase