Lead Data Scientist

HCA Healthcare; United States; On-site; USD 120,000 - 150,000; Full time

Job summary

A leading healthcare organization is seeking a Lead Data Scientist to design and implement data for feature engineering and machine learning. The ideal candidate will have 6+ years of experience, expertise in SQL and Python, and familiarity with healthcare data. This full-time position offers opportunities to work on innovative data products in a collaborative environment.

Qualifications

• 6+ years of experience in data science and machine learning.
• Expertise in SQL and Python.
• Experience with structured and unstructured data.
• Familiarity with healthcare domain knowledge preferred.

Responsibilities

• Design and implement data for feature engineering and machine learning.
• Create features with usable predictive power using domain knowledge.
• Conduct data exploration and analysis to identify patterns.
• Deploy code following best practices.

Skills

SQL

Python

Data processing and ETL tools

Data visualization tools

Experience with Docker

Cloud platforms (GCP)

Agile methodologies

Excellent communication skills

Tools

Apache Spark

Azure DevOps

Job description

Do you want to join an organization that invests in you as a Lead Data Scientist? At HCA, you come first. HCA Healthcare has committed up to $300 million in programs to support our incredible team members over the course of three years.

What you will do:

1. DATA INJECTION: Design and implement incoming data for feature engineering and machine learning.
2. FEATURE CREATION AND TRANSFORMATION: Create features with usable predictive power using domain knowledge of healthcare data, statistics, and data science.
3. FEATURE EXTRACTION AND SELECTION: Extract features via cluster analysis, text analytics, principal components analysis, and related methodologies to identify useful information without distorting original relationships or significant information, to improve model performance and scalability.
4. EXPLORATORY DATA ANALYSIS: Conduct data exploration and analysis to identify relevant patterns, trends, and relationships; understand the data deeply to align features with suitable machine learning methodologies.
5. MODEL EXPERIMENTATION: Apply various statistical and machine learning techniques to develop, tune, and optimize predictive models according to use case requirements.
6. DELIVERY: Deploy code following best practices.
7. DOCUMENTATION: Document and present data science strategies, insights, and solutions.
8. MONITORING: Build and maintain pipelines, code, and processes to ensure enterprise-grade data science product functionality.
9. DATA AND OUTPUT QUALITY: Ensure high quality and integrity throughout the data science process.
10. PRODUCT DEVELOPMENT MINDSET: Collaborate with stakeholders, data scientists, data engineers, and product managers to build and deliver high-quality data products.

What qualifications you will need:

• 6+ years of experience in data science and machine learning (for Lead level)
• Expertise in SQL and Python
• Experience with structured and unstructured data (tabular, text, images, video, etc.)
• Experience with SQL relational and non-relational databases
• Experience with data processing and ETL tools (e.g., Apache Spark)
• Experience with data visualization and monitoring tools
• Experience with modern software engineering practices (automated testing, CI/CD)
• Experience with Docker
• Experience with cloud platforms like GCP
• Experience with Agile methodologies and tools (e.g., Azure DevOps)
• Excellent communication and collaboration skills
• Ability to tell data-driven stories that drive action
• Preferred: Healthcare domain knowledge, familiarity with HL7, FHIR, DICOM, and healthcare regulatory aspects

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Information Technology, Engineering, and Research

Industries

• Technology, Information and Media, Software Development, IT Services, and Consulting

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