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Remote Mathematical Epidemiology Jobs (NOW HIRING)

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Research Scientist (Temporary), RGUD

Olympia, WA · On-site +1

This position is eligible to work fully remote in the US; work schedule required to overlap 50% of ... Master's degree in public health, epidemiology, statistics, biostatistics, math, economics ...

Vrtx

HEOR Modeling Director (Remote-Eligible)

Boston, MA · On-site +1

$204K - $306K/yr

... mathematics, statistics, economics, epidemiology) * Typically requires 10 years of relevant ... Remote-Eligible Flex Eligibility Status: In this Remote-Eligible role, you can choose to be ...

State of Washington

Data Specialist (DS2)

Olympia, WA · On-site +1

$95K - $125K/yr

Thurston County - Olympia, WA Job Type: Full Time - Non-Permanent Remote Employment: Flexible ... science, mathematics, computer science, statistics, biostatistics, epidemiology, or related ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... D. in a relevant field (such asEcology, Applied Mathematics, Statistics, Epidemiology (human or ...

Epistemix

Infrastructure Architect

Pittsburgh, PA · Remote

$67.50 - $86.50/hr

... Mathematics, Statistics, Epidemiology, or Public Health * Demonstrated experience managing or ... We are fully remote, with team members in the United States and Europe. Benefits include: * Equity ...

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Remote Mathematical Epidemiology information

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$45K

$85.2K

$133K

How much do remote mathematical epidemiology jobs pay per year?

As of Jul 15, 2026, the average yearly pay for remote mathematical epidemiology in the United States is $85,222.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $101,000.00 per year, depending on experience, location, and employer.

What are some typical challenges faced by remote mathematical epidemiologists, and how can they be addressed?

Remote mathematical epidemiologists often encounter challenges such as coordinating effectively with interdisciplinary teams across different time zones and managing large datasets securely from a home office. Clear communication, structured project management tools, and regular virtual meetings can help bridge gaps and maintain collaboration with public health officials, data scientists, and researchers. Additionally, setting up robust data security protocols and maintaining an organized workflow are essential for handling sensitive epidemiological data remotely. Proactively seeking feedback and sharing progress updates can foster a sense of connection and ensure alignment with broader project goals.

What are the key skills and qualifications needed to thrive as a Remote Mathematical Epidemiologist, and why are they important?

To thrive as a Remote Mathematical Epidemiologist, you need a strong background in mathematics, statistics, epidemiology, and often an advanced degree in a related field. Familiarity with statistical software (such as R, Python, or MATLAB), data visualization tools, and epidemiological modeling platforms is typically required. Excellent problem-solving skills, attention to detail, and the ability to communicate complex findings to non-specialists are vital soft skills. These competencies ensure accurate disease modeling, effective remote collaboration, and impactful public health recommendations.

What is the difference between Remote Mathematical Epidemiology vs Remote Data Analyst?

AspectRemote Mathematical EpidemiologyRemote Data Analyst
Required CredentialsAdvanced degrees in epidemiology, mathematics, or related fieldsBachelor's or master's in data science, statistics, or related fields
Work EnvironmentResearch-focused, often in public health or academic settingsBusiness, healthcare, or tech industries
Industry UsagePublic health agencies, research institutions, academiaCorporations, consulting firms, healthcare providers
Search & Comparison IntentUnderstanding specialized epidemiological modeling rolesAnalyzing data trends and insights in various sectors

Remote Mathematical Epidemiology involves developing models to understand disease spread, requiring advanced degrees and research experience. Remote Data Analysts focus on interpreting data to inform business or health decisions, often with a broader skill set. While both roles analyze data remotely, they serve different industries and require different credentials.

What is remote mathematical epidemiology?

Remote mathematical epidemiology is a field where professionals use mathematical models and statistical tools to study the spread of diseases, while working from a remote location. These experts analyze data, simulate outbreaks, and predict how diseases might progress in populations, often collaborating virtually with public health teams. Their work helps inform decisions about interventions such as vaccinations, social distancing, and resource allocation. Remote roles in this field have become more common due to advancements in technology and the increased availability of large datasets online.
More about Remote Mathematical Epidemiology jobs
What cities are hiring for Remote Mathematical Epidemiology jobs? Cities with the most Remote Mathematical Epidemiology job openings:
What are the most commonly searched types of Mathematical Epidemiology jobs? The most popular types of Mathematical Epidemiology jobs are:
What states have the most Remote Mathematical Epidemiology jobs? States with the most job openings for Remote Mathematical Epidemiology jobs include:
What job categories do people searching Remote Mathematical Epidemiology jobs look for? The top searched job categories for Remote Mathematical Epidemiology jobs are:
Remote Mathematical Epidemiology jobs near you
Infographic showing various Remote Mathematical Epidemiology job openings in the United States as of July 2026, with employment types broken down into 6% Locum Tenens, 81% Full Time, 11% Part Time, 1% Temporary, and 1% Contract. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution, with an average salary of $85,222 per year, or $41 per hour.
Senior Clinical Programmer Contractor

Senior Clinical Programmer Contractor

Arcus Biosciences

Remote

Full-time

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

Job description

Summary

The Senior Clinical Programmer Contractor will be responsible for support of team data review, data reconciliation and edit checks, and programming submission ready SDTM deliverables. This position will report to a Senior Manager of Clinical Programming or higher and will interact regularly with internal and external biostatisticians, clinical data managers, and other team members. Demonstrated ability to prioritize work and to effectively communicate and collaborate with key stakeholders both within Biometrics and beyond (research, translational science, clinical science, clinical operations and regulatory) is a must.
The ideal candidate will come with years of solid industry experience working in a regulated global environment while also demonstrating know-how, flexibility and scientific curiosity useful for establishing internal infrastructure, developing analysis standards, and driving both formal and exploratory work. 

Responsibilities

  • Working from specifications developed by Data Management, with some support build and execute programs for internal data reviews, data reconciliation, and edit checks.
  • Assist in developing/maintaining clinical programming related standards and tools.
  • Work with data management to review case report forms, database specifications and similar documents.
  • With some support, develop data transfer specifications and manage the transfer of external data.
  • Program SDTM datasets and produce related CDISC deliverables such as aCRF, define.xml, reviewer’s guide, etc.
  • With minimal supervision, performs stakeholder management, negotiating timelines and scope of deliverables.
  • Participate in standards governance and developing biometric department operational processes.

Qualifications 

  • Bachelor’s or Master’s degree in a data science field, e.g., statistics, mathematics, epidemiology, computer science, bioinformatics, or another field with commensurate levels of experience.
  • 4+ years of biotechnology or pharmaceutical experience, with (immuno-) oncology experience preferred.
  • Good programming experience in SAS.
  • Experience with other software languages (e.g., Unix scripts, AI tools, R functions/packages, etc).
  • Good knowledge of CDISC data standards (CDASH, SDTM).
  • Good knowledge of data standards and demonstrated experience in the handling of non-CRF data including proven ability to work with diverse data types, such as biomarker, PK/PD, pharmacovigilance, etc.
  • Demonstrated ability to rapidly adapt to changing project and strategic requirements.
  • Takes a fit-for-purpose mindset to daily work as well as long-term vision.

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