Data Scientist III

This role supports Kaiser Permanente’s statistical and data initiatives by contributing to data pipeline and automation development, creating problem statements and statistical models, and helping translate insights for production and stakeholder decision-making.

Location and Schedule

• Work location: Fulton, MD (onsite)
• Primary location: Maryland, Fulton, Maple Lawn Call Center
• Work schedule: Full-time
• Hours per week: 40
• Shift: Day
• Workdays: Mon, Tue, Wed, Thu, Fri
• Working hours: 09:00 AM to 05:00 PM
• Travel: No

Job Summary

Participate in the design and development of data pipelines and automation for data acquisition and ingestion. Develop problem statements, features, statistical models, and model validation for production use under guidance of more senior data scientists. Coordinate with stakeholders across domains to deliver statistically driven outcomes.

Core Responsibilities

• Build effective working relationships by proactively sharing resources, information, advice, and expertise.
• Listen to and act on performance feedback; provide mentoring to team members.
• Pursue self-development by creating plans to capitalize on strengths and address weaknesses, and influence others through technical explanations and examples.
• Adapt to change, challenges, and feedback by demonstrating flexibility and helping others adjust to new tasks and processes.
• Support others to meet business outcome needs.
• Complete assignments independently by applying current subject matter expertise to develop creative solutions while following procedures and policies and leveraging data and resources.
• Collaborate cross-functionally to solve business problems, escalate risks or issues as appropriate, and communicate progress and information.
• Support and monitor priorities, deadlines, and expectations.
• Identify and implement improvement opportunities for the team by speaking up with actionable recommendations.

Data, Modeling, and Production Work

• Develop detailed problem statements that outline hypotheses, scope, objectives, outcome statements, and metrics, including effects on target clients/customers.
• Under guidance of more senior data scientists, participate in designing and building data pipelines and automation to ingest raw data from multiple sources and formats by transforming, cleansing, and storing data for downstream consumption.
• Write and optimize diverse SQL queries and demonstrate working knowledge of database fundamentals.
• Analyze and investigate datasets using data visualization to summarize key characteristics, determine how to manipulate data to discover patterns, spot anomalies, test hypotheses, and check assumptions.
• Select, manipulate, and transform data into features for machine learning algorithms, applying methods such as dimensionality reduction, feature importance, and feature selection.
• Train statistical models under guidance by using algorithms and data mining techniques, testing models with various algorithms, and applying techniques to reduce overfitting such as cross-validation.
• Deploy and maintain reliable, efficient models through production.
• Verify model performance using model validation techniques to assess model fit quality, and leverage feedback and outputs to strengthen and improve performance.

Stakeholder Collaboration

• Work with internal and external stakeholders across domains to develop and deliver statistically driven outcomes by deriving insights from heterogeneous data, investigating problems across multiple use cases, driving informed decision-making, and presenting findings to technical and non-technical audiences.

Required Qualifications

• EDA and visualization: Minimum two (2) years experience working with Exploratory Data Analysis (EDA) and visualization methods.
• Machine learning/algorithms: Minimum one (1) year machine learning and/or algorithmic experience.
• Statistical analysis and modeling: Minimum two (2) years statistical analysis and modeling experience.
• Programming: Minimum two (2) years programming experience.
• Education and experience: Bachelors degree in Mathematics, Statistics, Computer Science, Engineering, Economics, Public Health, or related field AND Minimum three (3) years experience in data science or a directly related field.
• Substitutions: 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.

Technologies

• SQL
• Microsoft Excel
• Open Source Languages & Tools
• Relational Database Management
• Data Visualization Tools
• Business Intelligence Tools

Knowledge, Skills, and Abilities

Core:

• Ambiguity/Uncertainty Management
• Attention to Detail
• Business Knowledge
• Communication
• Critical Thinking
• Cross-Group Collaboration
• Decision Making
• Dependability
• Diversity, Equity, and Inclusion Support
• Drives Results
• Facilitation Skills
• Health Care Industry
• Influencing Others
• Integrity
• Learning Agility
• Organizational Savvy
• Problem Solving
• Short- and Long-term Learning & Recall
• Teamwork
• Topic-Specific Communication

Functional:

• Advanced Quantitative Data Modeling
• Algorithms
• Applied Data Analysis
• Business Intelligence Tools
• Data Ensemble Techniques
• Data Extraction
• Data Manipulation/Wrangling
• Data Visualization Tools
• Design Thinking
• Feature Analysis/Engineering
• Machine Learning
• Microsoft Excel
• Model Optimization
• Open Source Languages & Tools
• Relational Database Management

Preferred Qualifications

• One (1) year experience in a leadership role with or without direct reports.
• One (1) year healthcare experience.

Additional Role Details

• Employee status: Regular
• Employee group/union affiliation: NUE-PO-01|NUE|Non Union Employee
• Job level: Individual Contributor
• Job category: Data Analytics
• Department: Po/Ho Corp - 3YP Core - 0308

Compensation

Estimated salary range: USD 131,300 - 169,840 per year.