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About This Role
Thank you for considering a career at Ensemble!
Ensemble is a leading provider of technology\-enabled revenue cycle management solutions for health systems, including hospitals and affiliated physician groups. They offer end\-to\-end revenue cycle solutions as well as a comprehensive suite of point solutions to clients across the country.
Ensemble keeps communities healthy by keeping hospitals healthy. We recognize that healthcare requires a human touch, and we believe that every touch should be meaningful. This is why our people are the most important part of who we are. By empowering them to challenge the status quo, we know they will be the difference!
O.N.E Purpose:
- Customer Obsession: Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations.
- Embracing New Ideas: Continuously innovate by embracing emerging technology and fostering a culture of creativity and experimentation.
- Striving for Excellence: Execute at a high level by demonstrating our “Best in KLAS” Ensemble Difference Principles and consistently delivering outstanding results.
The Opportunity:
We’re solving problems in healthcare with AI.
Are you passionate about leveraging AI to solve complex problems in healthcare? Do you want to be part of a team that is transforming the industry with cutting\-edge technology? Join Ensemble Health Partners as an AI Engineer and make a meaningful impact on healthcare delivery and patient experience.
About Ensemble Health Partners
Ensemble Health Partners is at the forefront of healthcare innovation, investing over $70 million annually in technology research and development. With 11 technology patents and over 5,500 deployed AI models, we are dedicated to eliminating administrative complexity and reducing healthcare costs. Our team includes former employees from Google and Meta, and we operate with the entrepreneurial spirit of a start\-up backed by the scale and resources of a $1 billion company.
Why Join Us?
Purposeful Work Your work will directly contribute to reducing healthcare costs, improving care delivery and elevating the patient experience.
Innovative Environment We operate with the entrepreneurial spirit of a start\-up backed by the scale and resources of a $1 billion company.
Strong Client Base Our solutions are deployed across hundreds of hospitals and health systems, so ideas can quickly make an impact.
The Associate Data Scientist, AI will help develop and support machine learning and artificial intelligence solutions, including predictive analytics and generative AI applications. Working alongside data scientists, software engineers, and product teams, this role will assist with data analysis, model development, experimentation, and solution delivery.
This is an excellent opportunity for someone looking to grow their career in AI and machine learning while working on impactful healthcare challenges. The successful candidate should be eager to learn new technologies, comfortable working with data, and excited to contribute to a collaborative team environment.
Essential Job Functions
- Assist in developing, testing, and improving machine learning and AI models.
- Support data collection, preparation, transformation, and analysis activities.
- Participate in experiments and evaluations to identify opportunities for model improvement.
- Collaborate with product, engineering, and analytics teams on AI\-enabled solutions.
- Create reports, dashboards, and visualizations that communicate findings and insights.
- Contribute to documentation, presentations, and knowledge sharing within the team.
- Learn and apply best practices in machine learning, software development, and data science.
- Stay current on emerging AI, machine learning, and generative AI technologies.
Other Preferred Knowledge, Skills and Abilities
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field, or equivalent practical experience.
- Foundational knowledge of statistics, machine learning, and data analysis.
- Experience with Python, SQL, R, or similar programming languages through coursework, internships, research, or personal projects.
- Familiarity with machine learning frameworks such as Scikit\-learn, PyTorch, or TensorFlow.
- Interest in generative AI, large language models (LLMs), and retrieval\-augmented generation (RAG).
- Ability to work with structured and unstructured data.
- Strong problem\-solving and analytical thinking skills.
- Excellent written and verbal communication skills.
- Ability to work effectively both independently and within a collaborative team environment.
Desired Work Experience
- 0–2 years of experience in data science, machine learning, analytics, software engineering, or a related field.
- Relevant internships, research projects, graduate work, capstone projects, or personal projects are highly valued.
Compensation
- $25\.00 / hr
CAREER OPPORTUNITY OFFERING:
- Bonus Incentives
- Paid Certifications
- Tuition Reimbursement
- Comprehensive Benefits
- Career Advancement
Join an award\-winning company
- Five\-time winner of “Best in KLAS” 2020\-2022, 2024\-2025
- Black Book Research's Top Revenue Cycle Management Outsourcing Solution 2021\-2024
- 22 Healthcare Financial Management Association (HFMA) MAP Awards for High Performance in Revenue Cycle 2019\-2024
- Leader in Everest Group's RCM Operations PEAK Matrix Assessment 2024
- Clarivate Healthcare Business Insights (HBI) Revenue Cycle Awards for strong performance 2020, 2022\-2023
- Energage Top Workplaces USA 2022\-2024
- Fortune Media Best Workplaces in Healthcare 2024
- Monster Top Workplace for Remote Work 2024
- Great Place to Work certified 2023\-2024
- Innovation
- Work\-Life Flexibility
- Leadership
- Purpose \+ Values
- Innovation
- Work\-Life Flexibility
- Leadership
- Purpose \+ Values
Bottom line, we believe in empowering people and giving them the tools and resources needed to thrive. A few of those include:
Associate Benefits – We offer a comprehensive benefits package designed to support the physical, emotional, and financial health of you and your family, including healthcare, time off, retirement, and well\-being programs.
Our Culture – Ensemble is a place where associates can do their best work and be their best selves. We put people first, last and always. Our culture is rooted in collaboration, growth, and innovation.
Growth – We invest in your professional development. Each associate will earn a professional certification relevant to their field and can obtain tuition reimbursement.
Recognition – We offer quarterly and annual incentive programs for all employees who go beyond and keep raising the bar for themselves and the company.
Join an award\-winning company
Five\-time winner of “Best in KLAS” 2020\-2022, 2024\-2025
Black Book Research's Top Revenue Cycle Management Outsourcing Solution 2021\-2024
22 Healthcare Financial Management Association (HFMA) MAP Awards for High Performance in Revenue Cycle 2019\-2024
Leader in Everest Group's RCM Operations PEAK Matrix Assessment 2024
Clarivate Healthcare Business Insights (HBI) Revenue Cycle Awards for strong performance 2020, 2022\-2023
Energage Top Workplaces USA 2022\-2024
Fortune Media Best Workplaces in Healthcare 2024
Monster Top Workplace for Remote Work 2024
Great Place to Work certified 2023\-2024
- Innovation
- Work\-Life Flexibility
- Leadership
- Purpose \+ Values
Bottom line, we believe in empowering people and giving them the tools and resources needed to thrive. A few of those include:
- Associate Benefits – We offer a comprehensive benefits package designed to support the physical, emotional, and financial health of you and your family, including healthcare, time off, retirement, and well\-being programs.
- Our Culture – Ensemble is a place where associates can do their best work and be their best selves. We put people first, last and always. Our culture is rooted in collaboration, growth, and innovation.
- Growth – We invest in your professional development. Each associate will earn a professional certification relevant to their field and can obtain tuition reimbursement.
- Recognition – We offer quarterly and annual incentive programs for all employees who go beyond and keep raising the bar for themselves and the company.
Ensemble is an equal employment opportunity employer. It is our policy not to discriminate against any applicant or employee based on race, color, sex, sexual orientation, gender, gender identity, religion, national origin, age, disability, military or veteran status, genetic information or any other basis protected by applicable federal, state, or local laws. Ensemble also prohibits harassment of applicants or employees based on any of these protected categories.
Ensemble provides reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act and applicable state and local law. If you require accommodation in the application process, please contact [email protected].
This posting addresses state specific requirements to provide pay transparency. Compensation decisions consider many job\-related factors, including but not limited to geographic location; knowledge; skills; relevant experience; education; licensure; internal equity; time in position. A candidate entry rate of pay does not typically fall at the minimum or maximum of the role’s range.
Employment Disclaimers – Ensemble
Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Ensemble Health Partners, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 463 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $120,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Ensemble Health Partners AI Hiring
Ensemble Health Partners has 2 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Based in Blue Ash, OH, US. Compensation range: $95K - $95K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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