Data Scientist Iv - San Diego, United States - Kaiser Permanente

Mark Lane

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Mark Lane

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Description

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.


Essential Responsibilities:


  • Promotes learning in others by proactively providing and/or developing information, resources, advice, and expertise with coworkers and members; builds relationships with crossfunctional/external stakeholders and customers. Listens to, seeks, and addresses performance feedback; proactively provides actionable feedback to others and to managers. Pursues selfdevelopment; 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. Adopts new responsibilities; adapts to and learns from change, challenges, and feedback; demonstrates flexibility in approaches to work; champions change and helps others adapt to new tasks and processes. Facilitates team collaboration to support a business outcome.
  • 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.
  • Deploys and maintains reliable and efficient models through production.
  • Verifies model performance by demonstrating 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.
  • Collaborates with internal and external stakeholders across domains to develop and deliver statistical driven outcomes by delivering insights and values from heterogeneous data to investigate complex problems for multiple use cases; driving informed decisionmaking; and presenting findings to both technical and nontechnical audiences.

Minimum Qualifications:


  • Minimum three (3) years experience working with Exploratory Data Analysis (EDA) and visualization methods.
  • Minimum three (3) years machine learning and/or algorithmic experience.
  • Minimum three (3) years statistical analysis and modeling experience.
  • Minimum three (3) years programming experience.
  • Minimum one (1) year 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 five (5) 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): Advanced Quantitative Data Modeling; Algorithms; Applied Data Analysis; Data Extraction; Data Visualization Tools; Machine Learning; Relational Database Management; Microsoft Excel; Design Thinking; Business Intelligence Tools; Data Manipulation/Wrangling; Data Ensemble Techniques; Feature Analysis/Engineering; Open Source Languages & Tools; Model Optimization; Strategic Thinking; Deep Learning/Neural Networks; Project Management

PrimaryLocation :
California,San Diego,Mission Road Administration Building A

HoursPerWeek : 40


Shift :
Day


Workdays :
Mon, Tue, Wed, Thu, Fri

WorkingHoursStart : 08:01 AM

WorkingHoursEnd : 05:01 PM


Job Schedule :
Full-time


Job Type :
Standard


Employee Status :
Regular


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

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