Ascension

Data Scientist

Ascension • $96K — $134K *
US-AnywhereRemote in United States
Healthcare
Less than 5 years of experience
Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • High School diploma equivalency with 2 years of experience, Associate's/Bachelor's degree, or 4 years of applicable work experience required.
  • Bachelor's, Master's, or PhD in Data Science, Computer Science, Health Informatics, Statistics, or related STEM field preferred.
  • Familiarity with healthcare data standards and clinical coding structures is a plus.
  • Proficiency in Python (pandas, NumPy, scikit-learn) and knowledge of SQL.
  • Exposure to AI/NLP frameworks such as Hugging Face, LangChain, or Google Vertex AI.

Responsibilities

  • Assist in building, testing, and refining predictive machine learning models and Generative AI tools.
  • Extract, clean, and preprocess healthcare data, performing feature engineering.
  • Conduct model evaluation, benchmarking, and error analysis while assessing clinical safety and fairness.
  • Work alongside senior data scientists and clinical mentors to define analytics problems and technical tasks.
  • Write clean code and maintain project documentation to support model deployment and MLOps integration.

Benefits

  • Remote work opportunity.
  • Full-time day shift schedule for work-life balance.
  • Opportunity to work with senior data scientists and clinical professionals.
  • Engagement in meaningful projects addressing real-world clinical challenges.
Full Job Description
Your future role at a glance

Location: Remote

Department: Clinical and Population Health Analytic

Schedule: Full-time | Day shift

Salary: $96,208.99 - $134,109.89 per year

#ADSI #internalop

How you'll make an impact in this role

  • Build & Refine: Assist in building, testing, and refining predictive machine learning models and text-based Generative AI tools (utilizing Vertex AI and modern NLP frameworks) under the guidance of senior team members to address real-world clinical challenges.
  • Process & Analyze: Extract, clean, and preprocess structured healthcare data (EHR, billing, and claims), performing feature engineering to address noise, missingness, and complex clinical data structures.
  • Evaluate & Test: Conduct model evaluation, benchmarking, and error analysis, assessing performance metrics alongside clinical safety, fairness, and potential algorithmic bias.
  • Collaborate & Learn: Work alongside senior data scientists and clinical mentors to translate broad clinical questions into structured analytics problems and actionable technical tasks.
  • Document & Handoff: Write clean, well-documented code and maintain clear project documentation (in GitHub) to support model deployment and integration with MLOps pipelines.

What minimum requirements you'll need

Education:

  • High School diploma equivalency with 2 years of cumulative experience OR Associate'
    degree/Bachelor's degree OR 4 years of applicable cumulative job specific experience required.

What additional preferences we're seeking

  • Education: A Bachelor's, Master's, or PhD in Data Science, Computer Science, Health Informatics, Statistics, or a related STEM field. Healthcare Domain Interest: Familiarity with or strong eagerness to learn healthcare data standards and clinical coding structures (e.g., ICD-10, CPT codes).
  • Core Technical Skills: Solid foundational proficiency in Python (pandas, NumPy, scikit-learn), working knowledge of SQL (BigQuery/relational databases), and familiarity with version control tools like Git/GitHub. AI & NLP Exposure: Exposure to Large Language Model (LLM) concepts, prompt engineering, or modern NLP/GenAI frameworks (e.g., Hugging Face, LangChain, or Google Vertex AI) through coursework, research, internships, or projects.
  • Communication & Curiosity: Strong analytical problem-solving skills with the ability to communicate technical findings clearly to both technical peers and clinical stakeholders.

Responsibilities

  • Build & Refine: Assist in building, testing, and refining predictive machine learning models and text-based Generative AI tools (utilizing Vertex AI and modern NLP frameworks) under the guidance of senior team members to address real-world clinical challenges.
  • Process & Analyze: Extract, clean, and preprocess structured healthcare data (EHR, billing, and claims), performing feature engineering to address noise, missingness, and complex clinical data structures.
  • Evaluate & Test: Conduct model evaluation, benchmarking, and error analysis, assessing performance metrics alongside clinical safety, fairness, and potential algorithmic bias.
  • Collaborate & Learn: Work alongside senior data scientists and clinical mentors to translate broad clinical questions into structured analytics problems and actionable technical tasks.
  • Document & Handoff: Write clean, well-documented code and maintain clear project documentation (in GitHub) to support model deployment and integration with MLOps pipelines.


Qualifications

Education:

  • High School diploma equivalency with 2 years of cumulative experience OR Associate'
    degree/Bachelor's degree OR 4 years of applicable cumulative job specific experience required.

About Ascension

Ascension is a healthcare company that provides a range of services, including hospital care, primary care, and specialty care. The company operates more than 150 hospitals and 50 senior living facilities across the United States. Ascension also offers health insurance and other healthcare-related services. The company was founded in 1999 and is headquartered in St. Louis, Missouri.
Learn more about Ascension
Size
165,000 employees
Industry
Healthcare
Founded
1999
* Ladders Estimates

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