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Temporary Clinical Data Scientist Jobs (NOW HIRING)

Clinical Data Scientist

Redwood City, CA · On-site

$132K - $226K/yr

N-Power Medicine is seeking a Clinical Data Scientist to own the final stage of its clinical data pipeline, transforming complex datasets from manual abstraction, AI models, and electronic sources ...

Clinical Data Scientist

Redwood City, CA · On-site

$132K - $226K/yr

N-Power Medicine is seeking a Clinical Data Scientist to own the final stage of its clinical data pipeline, transforming complex datasets from manual abstraction, AI models, and electronic sources ...

Experience in molecular and clinical data analysis. * Experience in searching through and understanding scientific and regulatory literature. * Experience in working independently in a fast-paced ...

Experience in molecular and clinical data analysis. * Experience in searching through and understanding scientific and regulatory literature. * Experience in working independently in a fast-paced ...

Lead end-to-end medical research projects with top-tier life science companies. * Conduct EMR data exploration and extract relevant clinical features. * Apply LLM-based feature engineering to ...

Remote Duration 4-6 months The RBQM Data Scientist supports central monitoring and risk-based quality management (RBQM) for clinical trials. This role focuses on implementing and running pre-defined ...

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Temporary Clinical Data Scientist information

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How much do temporary clinical data scientist jobs pay per year?

As of Jul 15, 2026, the average yearly pay for temporary 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 are the key skills and qualifications needed to thrive as a Temporary Clinical Data Scientist, and why are they important?

To thrive as a Temporary Clinical Data Scientist, you need a solid background in statistics, data analysis, and clinical research, often supported by a degree in life sciences, statistics, or a related field. Familiarity with data management tools like SAS, R, Python, and clinical trials databases, as well as knowledge of GCP and regulatory compliance, is typically required. Strong analytical thinking, attention to detail, and effective collaboration skills help you stand out in this fast-paced, project-based role. These competencies are vital for ensuring accurate, compliant data analysis that supports timely and reliable clinical research outcomes.

What is a Temporary Clinical Data Scientist?

A Temporary Clinical Data Scientist is a professional hired on a short-term or contract basis to analyze and interpret clinical data, often for pharmaceutical, biotechnology, or healthcare organizations. Their main responsibilities include managing and validating clinical trial data, performing statistical analyses, and ensuring the integrity and accuracy of data used in research studies. They collaborate closely with clinical research teams to support evidence-based decisions and regulatory submissions. The temporary aspect allows organizations to address specific project needs or surges in workload without committing to a permanent hire.

What are some typical challenges faced by Temporary Clinical Data Scientists, and how can they effectively navigate them?

Temporary Clinical Data Scientists often face the challenge of quickly adapting to new teams, data systems, and study protocols. Because their contracts are short-term, they must efficiently learn organization-specific processes and contribute meaningful insights within a limited timeframe. Building strong communication with permanent staff and proactively seeking clarity on project goals can help overcome these hurdles. Additionally, staying organized and maintaining meticulous documentation ensures smooth handovers and project continuity.

What is the difference between Temporary Clinical Data Scientist vs Clinical Data Analyst?

AspectTemporary Clinical Data ScientistClinical Data Analyst
CredentialsTypically requires a degree in data science, biostatistics, or related field; familiarity with programming languages like R or PythonOften holds a degree in statistics, data analysis, or related field; proficiency in data management tools
Work EnvironmentContract-based, project-specific roles within clinical research or pharmaceutical companiesFull-time or part-time roles in healthcare, research institutions, or biotech firms
Employer & Industry UsageUsed by CROs, pharma companies, and research organizations for data modeling and analysisEmployed in hospitals, research centers, and biotech firms for data reporting and interpretation

While both roles involve analyzing clinical data, a Temporary Clinical Data Scientist focuses on advanced data modeling and predictive analytics on a contract basis, whereas a Clinical Data Analyst primarily handles data reporting and basic analysis in a more permanent or ongoing capacity.

What cities are hiring for Temporary Clinical Data Scientist jobs? Cities with the most Temporary Clinical Data Scientist job openings:
What are the most commonly searched types of Clinical Data Scientist jobs? The most popular types of Clinical Data Scientist jobs are:
What states have the most Temporary Clinical Data Scientist jobs? States with the most job openings for Temporary Clinical Data Scientist jobs include:
Clinical Data Scientist

Clinical Data Scientist

RedSail Technologies, LLC

Warrendale, PA • On-site, Remote

$130K - $160K/yr

Full-time

Posted 7 days ago


Job description

Clinical Data Scientist

Job Summary

The RedSail Technologies Network Services Business Unit has the primary mission to create incremental value streams for RedSail through the development and activation of Clinical, Financial, & Operational Programs that leverage our uniquely integrated technology platforms as well as our associated reach within the targeted market segments. The Clinical Data Scientist, will participate in the making use of RedSail’s data to evaluate and establish various impactful programs to accomplish and assist with the measurement of program effectiveness against the department objectives.

Key Duties

  • Data Collection: Gathering data from various sources, such as databases, APIs, web scraping, and more. This can involve collecting structured and unstructured data.
  • Data Cleaning: Preprocessing the collected data to handle missing values, remove duplicates, correct inconsistencies, and address outliers. This step ensures data quality and reliability.
  • Data Exploration (Exploratory Data Analysis, EDA): Analyzing the main characteristics of the data often through visualization and summary statistics. This helps in understanding data distributions, relationships between variables, and identifying patterns or anomalies.
  • Data Transformation: Modifying data into a suitable format for analysis, such as normalization, standardization, or creating new features (feature engineering).
  • Data Visualization: Creating visual representations of data, such as graphs, charts, and dashboards, to communicate findings effectively. Tools like Matplotlib, Seaborn, and Tableau are commonly used.
  • Statistical Analysis: Applying statistical methods to understand data distributions, test hypotheses, and infer relationships. This can include t-tests, chi-square tests, ANOVA, and regression analysis.
  • Data Communication: Presenting findings, insights, and recommendations to stakeholders through reports, presentations, and storytelling. Effective communication is crucial for decision-making.
  • Collaboration with Domain Experts: Working with professionals from various fields to ensure that the data science approach aligns with business goals and that the results are meaningful and actionable.
  • Keeping Up with Industry Trends: Continuously learning and adapting to new tools, technologies, and methodologies in data science to stay current and effective in the field.
  • Ethical Considerations and Compliance: Ensuring that data usage complies with ethical standards and legal regulations, such as data privacy laws (e.g., HIPAA)

Education/Training

  • Bachelor’s degree in Data Science, Data Engineering, or similar data relevant computer science/software development degree. Doctor of Pharmacy with data credentials or extensive data experience may substitute for formal education in Data Science.

Required Work Skills/Experience

  • Pharma/Pharmacy/Healthcare experience.
  • Experience programming with SQL scripting.
  • Experience with data analytics visualization tools such as PowerBI and Tableau.
  • Ability to transform complex data across multiple platforms into concise datasets.
  • Ability to visualize data in the most effective way possible for a given project or study.
  • Strong analytical and problem-solving skills; inquisitive.
  • Ability to work independently and with team members from different backgrounds and collaborative styles.
  • Excellent attention to detail with critical thinking skills.

Preferred Work Skills/Experience

  • A combination of both Doctor of Pharmacy and degree in Data Science, Data Engineering, or similar data relevant computer science/software development degree (i.e. Pharmacist Data Scientist) strongly preferred.
  • 2 years of experience as a Data Analyst, Data Scientist or Data Engineer.
  • Experience with Pharma/Pharmacy transactions.
  • Experience programming with Python or Go Lang.

Discretionary Judgement

  • Uses independent judgment and discretion based upon the employee’s experience in the position and knowledge of the products, equipment, and services.
  • Uses good judgment and possesses ethical work values.

Physical Demands/Working Conditions/General Employment

  • Moderate or high stress levels may be experienced in the job performance.
  • Position is performed in a general office environment, home office, or approved remote workspace where physical work includes, but is not limited to, sitting, standing, reaching, kneeling, bending, and lifting to 25 lbs.

Equipment

  • Daily use of Microsoft Teams (phone), computer, printer, and other routine office equipment.
  • Must have reliable and consistent internet access.

Safety to Self and Others

  • Little responsibility for the safety of others. Job is performed in an office setting where there are no hazardous materials or equipment.

Working Conditions/Hazards

  • Position is performed in an open office environment or approved remote work location.

Salary Range

  • $130,000-$160,000

Work Location

  • RedSail Office Hybrid

Benefits Include: PTO, 401k (5%) Match, Bonus Opportunities, Medical/Dental/Vision Insurance, Work-life balance, Health Clinic, Fitness Bonus and Professional Development.