Data Scientist V SSD (Durational 6 months to hire)

Key Skills

Algorithms, DevOps, Docker, Python Programming, PyTorch, R Programming, SQL

Job Description

This senior individual contributor is primarily responsible for leading the design and development of data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats. This role is also responsible for leading the development of detailed problem statements outlining hypotheses and their effect on target clients/customers, serving as an expert in the analysis and investigation of complex data sets, leading the selection, manipulation and transformation of data into features used in machine learning algorithms, training statistical models, leading the deployment and maintenance of reliable and efficient models through production, verifying and ensuring model performance, and partnering with internal and external stakeholders across domains to develop and deliver statistical driven outcomes.

Essential 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.

Minimum Qualifications:

• 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.

Additional 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 Qualifications:

• Two (2) years relational database experience.
• Four (4) years experience working with Open Source Tools (e g , R, Python).
• Two (2) years experience working with PyTorch.
• Two (2) years experience working with Docker.
• Two (2) years deep learning experience.
• Two (2) years experience in machine learning DevOps.
• Two (2) years experience working in big data or data engineering.
• Three (3) years experience working with Natural Language Processing.

Primary Location: California,San Diego,El Camino Real Administration

Scheduled Weekly Hours: 40

Shift: Day

Workdays: Mon, Tue, Wed, Thu, Fri

Working Hours Start: 08:00 AM

Working Hours End: 04:30 PM

Job Schedule: Full-time

Job Type: Standard

Employee Status: Regular

Employee Group/Union Affiliation: NUE-SCAL-01|NUE|Non Union Employee

Job Level: Individual Contributor

Specialty: Data Science

Department: Parsons West Annex - Prj Mgmt-Innovtn Proj-Qlty&Svc - 0806

Pay Range: $155000 - $200640 / year

The ranges posted above reflect the location in the job posting. The salary range may vary if you reside in a different location or state than the location posted.

Travel: Yes, 10 % of the Time

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 a diverse and inclusive workforce. Applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), age, sexual orientation, national origin, marital status, parental status, ancestry, disability, gender identity, veteran status, genetic information, other distinguishing characteristics of diversity and inclusion, or any other protected status.

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