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Healthcare Data Scientist Entry Level Jobs (NOW HIRING)

Tactile Medical

Data Scientist

Minneapolis, MN

... healthcare commercial data, intellectual curiosity, and the communication discipline to translate technical findings into commercial language Expert-level modern data science skills in Python and SQL ...

Easy Recruiter

Health Care Data Analyst - Remote

Health Care Data Analyst - Remote The Research Associate/Health Care Data Analyst provides high ... scientists, and data visualization specialists who conduct research, evaluation, and policy ...

Confluence Health

Healthcare Data Analyst

Wenatchee, WA ยท On-site

$30.21 - $48.21/hr

The Healthcare Data Analyst I designs and executes the analytics for a variety of project types. Coordinating with internal and external stakeholders, the Healthcare Data Analyst promotes using data ...

Cyber Resource

Healthcare Data Analyst

Richmond, VA

... Health Record system, and clinical data needs. Candidate must be able to work on site. Local ... care setting ยท Demonstrated ability to communicate clinical and data findings clearly to non ...

CVS Health

Data Scientist

New York, NY ยท On-site +1

$109K - $173K/yr

At CVS Health, you'll be surrounded by passionate colleagues who care deeply, innovate with purpose ... Data Scientist to participate in the development, validation, and delivery of algorithms ...

Healthcare Fraud Shield

Data Scientist

Chesterfield, MO ยท On-site +1

Headquarters Description Healthcare Fraud Shield is looking for a Data Scientist to join the team. Key Responsibilities * Provide technical contributions in a fast-paced R&D team environment to ...

Noblesoft Solutions

Data Scientist

Jacksonville, FL

... including Healthcare, Retail, Finance and Hospitality, adding tremendous value to those ... This is an entry level Data Scientist Role for a person who is self motivated and has a passion to ...

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Healthcare Data Scientist Entry Level information

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$46K

$165K

$243.5K

How much do healthcare data scientist entry level jobs pay per year?

As of Jun 27, 2026, the average yearly pay for healthcare data scientist entry level in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

How to get into data science in healthcare?

To enter healthcare data science as an entry-level professional, develop strong skills in programming languages like Python or R, and gain knowledge of healthcare data standards and electronic health records. Pursuing relevant education such as a degree in data science, statistics, or health informatics, along with certifications like Certified Health Data Analyst (CHDA), can improve job prospects. Gaining experience through internships or projects in healthcare settings helps build practical skills for this role.

Can I get a data scientist job with no experience?

Entry-level healthcare data scientist positions often require some knowledge of data analysis, programming languages like Python or R, and familiarity with healthcare data. While prior experience is not always mandatory, demonstrating relevant skills through coursework, certifications, or projects can improve chances of securing an entry-level role.

What is the difference between Healthcare Data Scientist Entry Level vs Healthcare Data Analyst?

AspectHealthcare Data Scientist Entry LevelHealthcare Data Analyst
Required CredentialsBachelor's degree in data science, statistics, or related field; familiarity with programming languages like Python or RBachelor's degree in health informatics, statistics, or related field; proficiency in data analysis tools
Work EnvironmentHealthcare organizations, research institutions, or tech companies focusing on healthcare data projectsHospitals, clinics, insurance companies, or healthcare consulting firms
Employer & Industry UsageUsed for developing predictive models, machine learning applications, and advanced analytics in healthcareUsed for reporting, data visualization, and basic analysis of healthcare data

The main difference between Healthcare Data Scientist Entry Level and Healthcare Data Analyst lies in the complexity of tasks and skill set. Data scientists focus on building models and advanced analytics, requiring programming and statistical expertise, while data analysts primarily handle data reporting and visualization. Both roles are essential in healthcare but serve different functions based on skill level and project scope.

How do I become a data scientist with no experience?

To become an entry-level healthcare data scientist with no experience, focus on building foundational skills in statistics, programming (such as Python or R), and data analysis. Gaining practical experience through online courses, certifications, and projects using real datasets can help demonstrate your abilities to employers.

Can a data scientist work in healthcare?

A healthcare data scientist applies data analysis, machine learning, and statistical skills to healthcare data to improve patient outcomes, optimize operations, and support medical research. They often work with electronic health records, medical imaging, and clinical data, requiring knowledge of healthcare regulations and tools like Python, R, and SQL. Entry-level roles may also require familiarity with healthcare-specific standards such as HL7 or FHIR.
More about Healthcare Data Scientist Entry Level jobs
What cities are hiring for Healthcare Data Scientist Entry Level jobs? Cities with the most Healthcare Data Scientist Entry Level job openings:
What are the most commonly searched types of Healthcare Data Scientist jobs? The most popular types of Healthcare Data Scientist jobs are:
What states have the most Healthcare Data Scientist Entry Level jobs? States with the most job openings for Healthcare Data Scientist Entry Level jobs include:
What job categories do people searching Healthcare Data Scientist Entry Level jobs look for? The top searched job categories for Healthcare Data Scientist Entry Level jobs are:
Healthcare Data Scientist Entry Level jobs near you
Infographic showing various Healthcare Data Scientist Entry Level job openings in the United States as of June 2026, with employment types broken down into 62% Full Time, 25% Part Time, and 13% Contract. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Data Scientist

Data Scientist

Tactile Medical

Minneapolis, MN

Other

Posted 12 days ago

Job description

Position Summary
The Marketing Data Scientist is the predictive intelligence engine of TCMD's Marketing and Market Access organization. The primary work is finding connections in TCMD's data that no one has looked for yet, building predictive models, and translating validated models into forward-looking tools. This individual synthesizes insights from Tactile's internal and external data platforms to develop and explore hypotheses for growth. The role's mission is to surface predictive insights from these systems that inform commercial strategy before decisions are finalized. This role collaborates closely with marketing and market access leadership along with sales excellence and commercial leadership.

Accountabilities & Responsibilities
Exploratory analysis, hypothesis generation, feature engineering, model construction, and validation
Build and validate predictive models using appropriate machine learning and statistical methodologies
Translating validated models into forward-looking dashboards or automated scoring systems that are consumed with ease by stakeholders
Partner across the marketing organization to develop campaign lift attribution; building causal inference models isolating incremental referral lift from specific marketing programs
Develop predictive analytics supporting payer targeting and coverage expansion opportunities
Train commercial team users on how to interpret and act on model outputs and the specific decisions the model is designed to support
Communicate within marketing and market access on status of model pipeline and backlog; routinely collect voice of internal stakeholder needs to drive continuous improvement in data driven decision making
Manage assigned projects to completion on time, within scope, and within budget.
Other duties as assigned.

Qualifications

Required:
Bachelor's degree in data science, statistics, mathematics, computer science, economics, or a quantitative field with strong statistical foundations
4-7 years applied data science or machine learning experience, applied in commercial or operational environments
Experience creating predictive models for non-data-scientists to make real commercial or operational decisions
Comfort with messy healthcare commercial data, intellectual curiosity, and the communication discipline to translate technical findings into commercial language
Expert-level modern data science skills in Python and SQL working with structured data and machine-learning frameworks; version-controlled code development and deployment
Ability to transform messy, real-world healthcare data with missing values, inconsistent coding, and multiple granularities into reliable predictive model inputs
Working knowledge of Salesforce CRM architecture, healthcare claims data, Power BI/Fabric deployment environments

Preferred:
Master's or PhD in quantitative field
Understanding of referral-based commercial models, payer coverage dynamics, prior authorization processes, and DME/medical device reimbursement
Survival analysis experience - has applied time-to-event modeling in a commercial context (e.g., customer churn, time-to-conversion, time-to-renewal). Particularly relevant for funnel stage duration modeling and HCP churn prediction
Salesforce data architecture familiarity - understands the Salesforce object model well enough to write efficient queries and build reliable features from CRM data without requiring a Salesforce administrator to extract data
Power BI or Tableau development experience sufficient to deploy model scoring outputs as operational dashboards
Experience in a B2B2C or referral-based commercial model where the customer and the end user are different

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