Interested in this Data Scientist role at Premier Inc.?
Apply Now →About This Role
Principal II Data Scientist What you will be doing:
This position will have responsibility for producing innovative solutions and thought leadership publications/patents driven by exploratory data analysis from complex and high\-dimensional datasets. Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement that makes Premier a thought leader. Use a flexible, analytical approach to design, develop, and evaluate methodologies and advanced algorithms that lead to clinically and operationally relevant end user analytics. Deploy knowledge of healthcare datasets, including electronic health record, administrative billing, and post\-adjudicated claims datasets. Work with subject matter experts, academic institutions, members and product engineers to translate prototypes into new products, services, and features.
Although not required, it is desired for the Principal, PINCAI Thought Leadership to have a clinical or public health background and understand how clinicians wish to deploy analytics in support of quality improvement and population health management applications. This level is recognized as expert in their field, knowledgeable of emerging trends and industry practices. Works without supervision with complete latitude for independent judgment. May mentor less experienced peers and display leadership as needed.
- Healthcare Analytics
- Advanced statistical and AI/ML Modeling
- Member and SME engagement
Key Responsibilities
Innovation and Modeling – 25%
- Work with internal and external SME’s to identify novel methodologies and AI/ML approaches to improve quality and efficiency across the healthcare system
- Work with developers and architects to translate prototypes into new products, services, and feature, and provide leadership and guidelines for large scale implementation
- Use a flexible, analytical approach to design, develop, and evaluate methodologies and advanced algorithms that lead to optimal value extraction from the data
- Produce innovative solutions driven by exploratory data analysis from complex and highly dimensional datasets
Modeling Strategy and Design – 20%
- Serves as a subject matter expert within various business domains (Cost, Clinical, MDM, etc.)
- Participate in data exploration and conceptual design for strategic initiatives
- Apply knowledge of statistics, machine learning, programming, data modeling, simulation and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement
- Generate and test hypotheses and analyze and interpret the results of product experiments
Requirements Analysis – 20%
- Facilitate \& lead meetings with the business/customers and IT teams to gather and document requirements
- Analyze business requirements, procedures and problems, design solutions and make recommendations
- Use clinical or technical background to interpret user needs and translate them into clinically meaningful methodologies and products
- Develop features and stories based on requirements to feed product backlogs
Publishing and Presentations – 15%
- Generate peer reviewed publications highlighting Premier’s innovative methodologies
- Create patent submissions to protect Premier’s intellectual property
- Publicly present innovative work at conferences and symposiums to demonstrate Premier’s thought
Knowledge Sharing – Operations – 10%
- Provide data, data relationships, and data science practice advice, demonstrations and presentations to colleagues, clients and management
- Provide mentoring and training
Data Operations \- 10%
- On your own or indirectly supervising teams to
+ Develop project estimates and work plans
+ Identifying, developing, reviewing, and evolving best practices, standards, operating procedures, and processes
+ Participating in the review of team member deliverables
Required Qualifications
Work Experience:
Years of Applicable Experience \- 10 or more years
Education:
Bachelors (Required) Preferred Qualifications
Skills:
- Strong business/healthcare analytics, statistics, simulation and advanced mathematics, data search and matching experience
- Facilitating requirements/gathering analysis with customers
- Excellent writing and speaking skills
- Technical data; SQL, data modeling
- Health care research experience, with large patient data sets
Experience:
- Strong business/healthcare analytics, statistics, simulation and advanced mathematics, data search and matching experience
- Software Design/development, statistics, AI/machine learning
- Proven track record publishing in high\-impact peer\-reviewed journals as first or lead author, and experience submitting patent applications
- Experience with customer engagement, collaboration and conflict management
- Experience teaching in a related domain in the university setting
Education:
- Master’s degree
Additional Job Requirements:
- Remain in a stationary position for prolonged periods of time
- Be adaptive and change priorities quickly; meet deadlines
- Attention to detail
- Operate computer programs and software
- Ability to communicate effectively with audiences in person and in electronic formats.
- Day\-to\-day contact with others (co\-workers and/or the public)
- Making independent decisions
- Ability to work in a collaborative business environment in close quarters with peers and varying interruptions
Working Conditions: Remote
Travel Requirements: Travel 1\-20% within the US
Physical Demands: Sedentary: Exerting up to 10 pounds of force occasionally, and/or a negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Sedentary work involves remaining stationary most of the time. Jobs are sedentary if movement is required only occasionally, and all other sedentary criteria are met.
Premier’s compensation philosophy is to ensure that compensation is reasonable, equitable, and competitive in order to attract and retain talented and highly skilled employees. Premier’s internal salary range for this role is $141,000 \- $234,000\. Final salary is dependent upon several market factors including, but not limited to, departmental budgets, internal equity, education, unique skills/experience, and geographic location. Premier utilizes a wide\-range salary structure to allow base salary flexibility within our ranges.
Qualified full\-time and part\-time employees also receive access to the following benefits:
- Health, dental, vision, life and disability insurance
- 401k retirement program
- Paid time off
- Participation in Premier’s employee incentive plans
- Tuition reimbursement and professional development opportunities
Premier at a glance:
- Granted World's Most Ethical Companies, Ethisphere, 2008\-2026
- Named U.S. News \& World Report, Best Companies to Work For (2023, 2024, 2025\)
- Accredited by Forbes: America’s Best Management Consulting Firms 2024\-2025
- Given Modern Healthcare Best in Business Awards: Consultants\- Healthcare Management
- Awarded Cigna Workforce Designation Gold Level Recipient (2016,2017,2019,2020,2021,2022,2023,2025\)
For a listing of all of our awards, please visit the Awards and Recognition section on our company website.
Employees receive:
- Perks and discounts
- Access to on\-site and online exercise classes
Premier is looking for smart, agile individuals like you to help us transform the healthcare industry. Here you will find critical thinkers who have the freedom to make an impact. Colleagues who share your thirst to learn more and do things better. Teammates committed to improving the health of a nation. See why incredible challenges require incredible people.
Premier is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to unlawful discrimination because of their age, race, color, religion, national origin, ancestry, citizenship status, sex, sexual orientation, gender identity, gender expression, marital status, familial status, pregnancy status, genetic information, status as a victim of domestic violence, covered military or protected veteran status (e.g., status as a Vietnam Era veteran, disabled veteran, special disabled veteran, Armed Forces Serviced Medal veteran, recently separated veteran, or other protected veteran) disability, or any other applicable federal, state or local protected class, trait or status or that of persons with whom an applicant associates. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. In addition, as a federal contractor, Premier complies with government regulations, including affirmative action responsibilities, where they apply. EEO / AA / Disabled / Protected Veteran Employer.
Premier also provides reasonable accommodations to qualified individuals with a disability or those who have a sincerely held religious belief. If you need assistance in the application process, please reply to diversity\_and\[email protected] or contact Premier Recruiting at 704\.357\.0022\.
*Personal Information submitted will be processed in accordance with* *Premier's Employee and Job Applicant Privacy Notice**, which includes additional information about your privacy rights.*
Salary Context
This $141K-$234K range is above the median for Data Scientist roles in our dataset (median: $160K across 258 roles with salary data).
View full Data Scientist salary data →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 4,317 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Premier Inc., 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 in Demand for This Role
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 789 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $141K to $234K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Premier Inc. AI Hiring
Premier Inc. has 3 open AI roles right now. They're hiring across Data Scientist. Based in Remote, US. Compensation range: $120K - $234K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.