Data Scientist III at Kaiser Permanente Oakland, CA

Data Scientist III – Kaiser Permanente

Location:

Oakland, California

Recruitment Number: 1355343

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 formats under the guidance of more senior data scientists. The role also includes developing detailed problem statements outlining hypotheses and their effect on target clients/customers, analysing and investigating data sets, summarising 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 working with internal and external stakeholders across domains to develop and deliver statistically‑driven outcomes.

• Build effective relationships with others by proactively providing resources, information, advice and expertise to coworkers and members. Listen to, seek and address performance feedback; provide mentoring to team members. Pursue self‑development by creating plans and taking action to capitalize on strengths and develop weaknesses; influence others through technical explanations and examples. Adapt to and learn from change, challenges and feedback; demonstrate flexibility in approaches to work;
  
  help others adapt to new tasks and processes. Support and respond to the needs of others to support business outcomes.
• Complete work assignments autonomously by applying up‑to‑date expertise in the subject area to generate creative solutions; ensure all procedures and policies are followed; leverage an understanding of data and resources to support projects or initiatives. Collaborate cross‑functionally to solve business problems; escalates issues or risks as appropriate; communicate progress and information. Support, identify and monitor priorities, deadlines and expectations. Identify, speak up and implement ways to address improvement opportunities for the team.
• Develop detailed problem statements outlining hypotheses and their effect on target clients/customers by defining scope, objectives, outcome statements and metrics.
• Participate in the design and development of data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and formats under the guidance of more senior data scientists by transforming, cleansing and storing data for consumption by downstream processes; writing and optimising diverse SQL queries; and demonstrating a working knowledge of database fundamentals.
• Analyse and investigate data sets and summarise key characteristics by employing data visualisation methods; determine how best to manipulate data sources to discover patterns, spot anomalies, test hypotheses and/or check assumptions.
• Select, manipulate and transform data into features used in machine‑learning algorithms by leveraging techniques to conduct dimensionality reduction, feature importance and feature selection.
• Train statistical models under the guidance of more senior data scientists 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.
• Deploy and maintain reliable and efficient models through production.
• Verify model performance by demonstrating a working knowledge 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.
• Work with internal and external stakeholders across domains to develop and deliver statistically‑driven outcomes by delivering insights and value from heterogeneous data to investigate problems for multiple use cases; driving informed decision‑making; and presenting findings to both technical and non‑technical audiences.

• Minimum 2 years experience working with exploratory data analysis (EDA) and visualisation methods.
• Minimum 1 year machine‑learning…