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About This Role
Location: Hybrid, NY
Medidata follows a hybrid office policy in which employees who are hired for an in\-person position are expected to work on site a certain number of days per week following Company policy.
About our Company:
Medidata is powering smarter treatments and healthier people through digital solutions to support clinical trials. Celebrating over 25 years of ground\-breaking technological innovation across more than 38,000 trials and 12 million patients, Medidata offers industry\-leading expertise, analytics\-powered insights, and one of the largest clinical trial data sets in the industry. More than 1 million registered users across approximately 2,300 customers trust Medidata's seamless, end\-to\-end platform to improve patient experiences, accelerate clinical breakthroughs, and bring therapies to market faster. A Dassault Systèmes brand (Euronext Paris: FR0014003TT8, DSY.PA), Medidata is headquartered in New York City and has been recognized as a Leader by Everest Group and IDC. Discover more at www.medidata.com. Listen to our latest podcast, from Dreamers to Disruptors, and follow us at @Medidata
About the Team:
Medidata AI organization is building pioneer innovative AI products based on the largest collection of clinical data in the world. Our AI teams are staffed with passionate technology and scientific experts looking to solve the most complex questions facing drug development through the use of machine learning and AI.
We are looking for individuals who will solve the most complex questions facing the industry today with innovative ML techniques based on both classical and GenAI approaches. The AI features developed will power modern clinical trial study design and study conduct with Rave and Patient Cloud products. This role will report to the Director of Data Science, and partner heavily with all of the key stakeholder functions including Data Science, Product, and Engineering.
Responsibilities:
You are an experienced Data Scientist who will design, implement, and productionize new AI driven features integrated with Medidata products
- Design, develop and validate machine learning models for novel clinical trial applications.
- Interact with product team to grasp product needs and provide AI solution (data, modeling strategies, and model serving).
- Develop prototypes that communicate how models can be used within customer facing products
- Evaluate and assess novel tools, algorithms, and technologies to be an AI community enabler.
- Build end\-to\-end machine learning pipelines from data curation, processing, model building, model evaluation, to model deployment for production.
- Lead implementations of AI tasks and drive technical decisions across teams.
Qualifications:
- Bachelor's, Master's or PhD is required in a computational field such as Data Science, Computer Science, Mathematics, Statistics, or related field and a minimum of 2 years of experience
- Proficiency using Python, SQL, Linux shell scripting, AWS, Docker, and Git
- Experience with AI service development, familiar with different model serving strategies and service basics (performance, latency, scalability, etc)
- Technical leadership in both hard and soft skills, proactive, clear, and efficient in communication
- Experience with deep learning is preferred
- Previous experience with deploying GPU based models to AWS is a plus
*Nice to have(s) but not required...*
- Experience with LLM or transformer based algorithms and methods
- Familiarity with NLP in healthcare data datasets in production
- Familiarity with machine learning infrastructure and frameworks, CI/CD, and MLOps
As with all roles, Medidata sets ranges based on a number of factors including function, level, candidate expertise and experience, and geographic location. Pay ranges for candidates in locations other than New York City, may differ based on the local market data in that region.
The salary range for positions that will be physically based in New York Metro Area is $96,000\-$128,000
Base pay is one part of the Total Rewards that Medidata provides to compensate and recognize employees for their work. Most sales positions are eligible for a commission on the terms of applicable plan documents, and many of Medidata's non\-sales positions are eligible for annual bonuses. Medidata believes that benefits should connect you to the support you need when it matters most and provides benefits, including medical, dental, life and disability insurance, 401(k) matching, family leave, flexible paid time off; and 10 paid holidays per year.
Equal Employment Opportunity:
In order to provide equal employment and advancement opportunities to all individuals, employment decisions at Medidata are based on merit, qualifications and abilities. Medidata is committed to a policy of non\-discrimination and equal opportunity for all employees and qualified applicants without regard to race, color, religion, gender, sex (including pregnancy, childbirth or medical or common conditions related to pregnancy or childbirth), sexual orientation, gender identity, gender expression, marital status, familial status, national origin, ancestry, age, disability, veteran status, military service, application for military service, genetic information, receipt of free medical care, or any other characteristic protected under applicable law. Medidata will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.
*We will accept applications on an ongoing basis until we fill the position.*
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Inclusion statement
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In order to provide equal employment and advancement opportunities to all individuals, employment decisions at 3DS are based on merit, qualifications and abilities. 3DS is committed to a policy of non\-discrimination and equal opportunity for all employees and qualified applicants without regard to race, color, religion, gender, sex (including pregnancy, childbirth or medical or common conditions related to pregnancy or childbirth), sexual orientation, gender identity, gender expression, marital status, familial status, national origin, ancestry, age (40 and above), disability, veteran status, military service, application for military service, genetic information, receipt of free medical care, or any other characteristic protected under applicable law. 3DS will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state laws and local ordinances. We are committed to fair employment practices and will evaluate all candidates based on their qualifications, regardless of past arrest or conviction history.
Salary Pay Transparency
Compensation for the role will be commensurate with experience. The total expected compensation range will be between $96000 and $128000, representing the base salary (or annualized salary based on estimated hourly compensation) and target bonus.
Salary Context
This $96K-$128K range is in the lower quartile for Data Scientist roles in our dataset (median: $157K across 236 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 3,823 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Medidata Solutions, 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 $198,000 based on 808 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($112K) sits 43% below the category median. Disclosed range: $96K to $128K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Medidata Solutions AI Hiring
Medidata Solutions has 2 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer. Based in New York, NY, US. Compensation range: $128K - $180K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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