Data Scientist IV
1 day ago
About Kaiser Permanente
Kaiser Permanente is a leading healthcare organization that values innovation and data-driven decision making. As a Data Scientist IV, you will play a critical role in developing and deploying machine learning models to improve patient outcomes and drive business growth.
Job Summary
This individual contributor is primarily responsible for designing and developing data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats by transforming, cleansing, and storing data for consumption. This role is also responsible for developing detailed problem statements outlining hypotheses and their effect on target clients/customers, analyzing and investigating complex data sets and summarizing key characteristics, selecting, manipulating and transforming data into features used in machine learning algorithms, training statistical models, deploying and maintaining reliable and efficient models through production, verifying model performance, and collaborating with internal and external stakeholders across domains to develop and deliver statistical driven outcomes.
Responsibilities
- Promotes learning in others by proactively providing and/or developing information, resources, advice, and expertise with coworkers and members; builds relationships with cross-functional/external stakeholders and customers. Listens to, seeks, and addresses performance feedback; proactively provides actionable feedback to others and to managers. Pursues self-development; creates and executes plans to capitalize on strengths and develop weaknesses; leads by influencing others through technical explanations and examples and provides options and recommendations.
- Completes work assignments autonomously and supports business-specific projects by applying expertise in subject area and business knowledge to generate creative solutions; encourages team members to adapt to and follow all procedures and policies. Collaborates cross-functionally and/or externally to achieve effective business decisions; provides recommendations and solves complex problems; escalates high-priority issues or risks, as appropriate; monitors progress and results. Supports the development of work plans to meet business priorities and deadlines; identifies resources to accomplish priorities and deadlines.
- Develops detailed problem statements outlining hypotheses and their effect on target clients/customers by defining scope, objectives, outcome statements and metrics.
- Designs and develops data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats by transforming, cleansing, and storing data for consumption by downstream processes; writing and optimizing diverse SQL queries; and demonstrating advanced knowledge of database fundamentals.
- Analyzes and investigates complex data sets and summarizes key characteristics by employing data visualization methods; and determining how best to manipulate data sources to discover patterns, spot anomalies, test hypotheses, and/or check assumptions.
- Selects, manipulates, and transforms data into features used in machine learning algorithms by leveraging techniques to conduct dimensionality reduction, feature importance, and feature selection.
- Trains statistical models by using algorithms and data mining techniques; testing models with various algorithms to assess the input dataset and related features; and applying techniques to prevent overfitting such as cross-validation.
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