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Data Scientist II

Primary Location Oakland, California Worker Location Remote Job Number 1352749 Date posted 05/05/2025
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Description:
Overview: 

The Entry-Level Data Scientist will support Government Programs’ Risk Adjustment team by applying foundational data science skills to analyze healthcare data and contribute to data-driven solutions. This role offers the opportunity to work with Medicare Advantage, ACA, and Medicaid data, supporting efforts to improve risk score accuracy, ensure regulatory compliance, and enhance program performance.

Working under the guidance of senior data scientists, this role involves using Python and cloud-based analytics tools to clean, analyze, and visualize data from sources such as claims, encounter, and enrollment records. The ideal candidate has a degree in data science or a related field, exposure to machine learning and statistical techniques, and a strong interest in applying data to real-world healthcare challenges.

This is a collaborative role with opportunities to learn from experienced team members while contributing to impactful projects that support data-informed decision-making across clinical, actuarial, and operational teams.



Job Summary:

This individual contributor is primarily responsible for participating in the design and development of data pipelines, automation for data acquisition, and ingestion of raw data from multiple data sources and data formats under the guidance of more senior data scientists. This role is also responsible for assisting in the development of detailed problem statements outlining hypotheses and their effect on target clients/customers, Analyzing and investigating data sets and summarizing key characteristics, selecting, manipulating and transforming data into features used in machine learning algorithms under the guidance of more senior data scientists, training statistical models under the guidance of more senior data scientists, assisting with the deployment and maintenance of reliable and efficient models through production, examining model performance, and working with internal and external stakeholders under the guidance of more senior data scientists to develop and deliver statistical driven outcomes.



Essential Responsibilities:


  • Pursues effective relationships with others by sharing resources, information, and knowledge with coworkers and members. Listens to, addresses, and seeks performance feedback. Pursues self-development; acknowledges strengths and weaknesses based on career goals and takes appropriate development action to leverage / improve them. Adapts to and learns from change, challenges, and  feedback; demonstrates flexibility in approaches to work. Assesses and responds to the needs of others to support a business outcome.

  • Completes work assignments by applying up-to-date knowledge in subject area to meet deadlines; follows procedures and policies, and applies data and resources to support projects or initiatives with limited guidance and/or sponsorship. Collaborates with others to solve business problems; escalates issues or risks as appropriate; communicates progress and information. Supports the completion of priorities, deadlines, and expectations. Identifies and speaks up for ways to address improvement opportunities.

  • Assists in the development of detailed problem statements outlining hypotheses and their effect on target clients/customers by defining scope, objectives, outcome statements and metrics under the guidance of more senior data scientists.

  • Participates in the design and development of data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats under the guidance of more senior data scientists by transforming, cleansing, and storing data for consumption by downstream processes; writing diverse SQL queries; and demonstrating a working knowledge of database fundamentals.

  • Analyzes and investigates 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 under the guidance of more senior data scientists by leveraging techniques to conduct dimensionality reduction, feature importance, and feature selection.

  • Trains 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.

  • Assists with the deployment and maintenance of reliable and efficient models through production.

  • Examines model performance by demonstrating a working knowledge of a variety of model validation techniques to assess and discriminate the goodness of model fit; and identifying feedback and output to inform and strengthen model performance.

  • Works with internal and external stakeholders under the guidance of more senior data scientists to develop and deliver statistical driven outcomes by providing insights and values from heterogeneous data to investigate problems for use cases; and supporting informed decision-making.

Minimum Qualifications:


  • Minimum one (1) year statistical analysis and modeling experience.

  • Minimum one (1) year programming experience.

  • Bachelors degree in Mathematics, Statistics, Computer Science, Engineering, Economics, Public Health, or related field OR Minimum two (2) years experience in data science or a directly related field. Advanced degrees may be substituted for the work experience requirements.


Additional Requirements:

  • Knowledge, Skills, and Abilities (KSAs): Advanced Quantitative Data Modeling; Applied Data Analysis; Data Extraction; Data Visualization Tools; Relational Database Management; Microsoft Excel; Design Thinking; Business Intelligence Tools; Data Manipulation/Wrangling; Open Source Languages & Tools; Model Optimization; Algorithms; Machine Learning; Data Ensemble Techniques; Feature Analysis/Engineering
Preferred Qualifications:
  • One (1) year healthcare experience.
  • One (1) year relational database experience.
  • One (1) year experience working with SQL.
  • One (1) year experience working with Open Source Tools (e g , R, Python).
  • One (1) year experience working with Scikit-Learn.
  • One (1) year experience working with Excel.
  • One (1) year study design experience.
  • One (1) year experience working in big data or data engineering.
  • One (1) year experience working with causal inference.
  • One (1) year data simulation experience.
Primary Location: California,Oakland,1800 Harrison Scheduled Weekly Hours: 40 Shift: Day Workdays: Mon, Tue, Wed, Thu, Fri Working Hours Start: 08:00 AM Working Hours End: 05:00 PM Job Schedule: Full-time Job Type: Standard Worker Location: Remote Employee Status: Regular Employee Group/Union Affiliation: NUE-PO-01|NUE|Non Union Employee Job Level: Individual Contributor Specialty: Data Science Department: Po/Ho Corp - Risk Adj Reporting Analytics - 0308 Pay Range: $112200 - $145200 / year Kaiser Permanente strives to offer a market competitive total rewards package and is committed to pay equity and transparency. The posted pay range is based on possible base salaries for the role and does not reflect the full value of our total rewards package. Actual base pay determined at offer will be based on labor market data and a candidate's years of relevant work experience, education, certifications, skills, and geographic location. Travel: No Remote: Work location is the remote workplace (from home) within KP authorized states. Worker location must align with Kaiser Permanente's Authorized States policy. At Kaiser Permanente, equity, inclusion and diversity are inextricably linked to our mission, and we aim to make it a part of everything we do. We know that having a diverse and inclusive workforce makes Kaiser Permanente a better place to receive health care, a more supportive partner in our communities we serve, and a more fulfilling place to work. Working at Kaiser Permanente means that you agree to and abide by our commitment to equity and our expectation that we all work together to create an inclusive work environment focused on a sense of belonging and wellbeing.

Kaiser Permanente is an equal opportunity employer committed to fair, respectful, and inclusive workplaces. Applicants will be considered for employment without regard to race, religion, sex, age, national origin, disability, veteran status, or any other protected characteristic or status. Submit Interest