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Clinical Data Scientist Jobs (NOW HIRING)

Medpace, Inc.

AI Data Scientist

Cincinnati, OH

The AI Data Scientist will support various projects across the company to bring data sources ... This team supports many teams across the business including clinical operations, medical, labs ...

Medpace, Inc.

AI Data Scientist

Cincinnati, OH · On-site

The AI Data Scientist will support various projects across the company to bring data sources ... This team supports many teams across the business including clinical operations, medical, labs ...

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$37.5K

$122.7K

$196.5K

How much do clinical data scientist jobs pay per year?

As of May 28, 2026, the average yearly pay for clinical data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a Clinical Data Scientist job?

A Clinical Data Scientist analyzes healthcare and clinical trial data to extract insights that support medical research, drug development, and patient outcomes. They use statistical models, machine learning, and programming skills to interpret complex datasets and improve decision-making in clinical settings. Their work helps optimize trial designs, identify treatment patterns, and ensure data quality and regulatory compliance.

What are the key skills and qualifications needed to thrive in the Clinical Data Scientist position, and why are they important?

To thrive as a Clinical Data Scientist, you need a strong background in statistics, data analysis, clinical research, and often a degree in life sciences, biostatistics, or a related field. Familiarity with programming languages such as Python or R, knowledge of clinical trial management systems (CTMS), and certifications like SAS or Clinical Data Management are highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills are essential for collaborating with healthcare professionals and sharing data-driven insights. These skills help ensure the accurate interpretation and proper management of complex clinical data, which supports evidence-based decision making in healthcare.

What are the main challenges Clinical Data Scientists face in their day-to-day work?

Clinical Data Scientists often encounter challenges such as handling large, complex datasets from multiple sources, ensuring data quality and integrity, and staying compliant with strict regulatory standards like HIPAA or FDA guidelines. They must also translate clinical requirements into analytical models, which requires close collaboration with clinicians, biostatisticians, and IT teams. Balancing detailed statistical analysis with clear, actionable reporting is key, and adapting to evolving technologies and new data sources is a common part of the job. Successfully overcoming these challenges supports clinical research outcomes and helps advance patient care.
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Clinical Data Scientist jobs near you
Infographic showing various Clinical Data Scientist job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $122,738 per year, or $59 per hour.
Clinical Data Scientist - AI Trainer

Clinical Data Scientist - AI Trainer

DataAnnotation

Nevada, IA • On-site, Remote

$60/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real‐world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state‐of‐the‐art AI models on tasks like evaluating AI‐generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full‐time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, up to $60 USD/hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI‐generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data‐driven insights, for technical accuracy and real‐world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well‐documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end‐to‐end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #J-18808-Ljbffr

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