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Remote Edc Programmer Jobs in New York (NOW HIRING)

Remote Duration 4-6 months The RBQM Data Scientist supports central monitoring and risk-based ... SAS programming to deliver robust and scalable analytics across multiple studies. KEY ...

Remote work options may be considered on a case-by-case basis and if approved by the Company. About ... EDC), eSource and/or External Data Stream systems at the trial and/or program level. This position ...

Remote Edc Programmer information

What is the difference between Remote Edc Programmer vs Remote Clinical Data Coordinator?

AspectRemote Edc ProgrammerRemote Clinical Data Coordinator
Required CredentialsTypically requires a degree in computer science, life sciences, or related field; proficiency in EDC systemsUsually requires a degree in health sciences, life sciences, or related; knowledge of clinical data management
Work EnvironmentPrimarily focused on programming and system setup within clinical trialsOversees data collection, entry, and quality control in clinical studies
Employer & Industry UsagePharmaceutical companies, CROs, biotech firmsPharmaceutical companies, CROs, research institutions

The Remote Edc Programmer primarily focuses on designing and programming electronic data capture systems for clinical trials, requiring technical programming skills. In contrast, the Remote Clinical Data Coordinator manages data collection and quality assurance processes. Both roles are essential in clinical research but differ in technical focus and daily responsibilities.

What is a Remote EDC Programmer?

A Remote EDC Programmer is a professional who designs, develops, and manages Electronic Data Capture (EDC) systems for clinical trials or research studies, working from a remote location. They are responsible for programming databases, building electronic case report forms (eCRFs), and ensuring that data collection processes meet regulatory and quality standards. EDC Programmers collaborate with clinical teams to customize systems according to study protocols and troubleshoot technical issues to ensure smooth data collection and management. Their remote role allows them to work with organizations and clients globally, leveraging secure communication and data tools.

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

To thrive as a Remote EDC (Electronic Data Capture) Programmer, you need a solid background in clinical data management, database design, and programming languages such as SQL, often supported by a degree in computer science or a related field. Familiarity with EDC systems like Medidata Rave, Oracle InForm, and knowledge of relevant regulatory standards (e.g., CDISC, FDA 21 CFR Part 11) are typically required. Strong problem-solving skills, attention to detail, and effective communication are essential soft skills for collaborating remotely with cross-functional clinical teams. These skills ensure accurate data capture, regulatory compliance, and efficient study execution in clinical trials.

What are some common challenges Remote EDC Programmers face when collaborating with cross-functional teams, and how can they overcome them?

Remote EDC Programmers often work closely with data managers, clinical trial coordinators, and statisticians, which can present challenges such as time zone differences, communication barriers, and varying technical expertise. Overcoming these challenges typically involves using clear documentation, regular virtual check-ins, and collaborative platforms to ensure alignment on project goals and timelines. Building strong relationships with team members and proactively addressing issues can also help ensure smooth collaboration and successful study database development.
What cities in New York are hiring for Remote Edc Programmer jobs? Cities in New York with the most Remote Edc Programmer job openings:
Data Scientist

Data Scientist

MM International

New York, NY • Remote

Contractor

Re-posted 5 days ago


Job description

Title:  Data Scientist

Location:  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 KRIs, QTLs, and other risk metrics using clinical data, with strong emphasis on SAS programming to deliver robust and scalable analytics across multiple studies.
KEY RESPONSIBILITIES:
The RBQM Data Scientist may perform a range of the following responsibilities, depending upon the studies’ complexity and studies’ development stage:
• Implement and maintain pre-defined KRIs, QTLs, and triggers using robust SAS programs/macros across multiple clinical studies.
• Extract, transform, and integrate data from EDC systems (e.g., RAVE) and other clinical sources into analysis-ready SAS datasets.
• Run routine and ad-hoc RBQM/central monitoring outputs (tables, listings, data extracts, dashboard feeds) to support signal detection and study review.
• Perform QC and troubleshooting of SAS code; ensure outputs are accurate and efficient.
• Maintain clear technical documentation (specifications, validation records, change logs) for all RBQM programs and processes.
• Collaborate with Central Monitors, Central Statistical Monitors, Data Management, Biostatistics, and Study Operations to understand requirements and ensure correct implementation of RBQM metrics.
Qualifications
Education & Experience
• PhD, MS, or BA/BS in statistics, biostatistics, computer science, data science, life science, or a related field.
• Relevant clinical development experience (programming, RBM/RBQM, Data Management), for example:
o PhD: 3+ years
o MS: 5+ years
o BA/BS: 8+ years
Technical – Required
• Advanced SAS programming skills (hard requirement) in a clinical trials environment (Base SAS, Macro, SAS SQL; experience with large, complex clinical datasets).
• Hands-on experience working with clinical trial data.
• Proficiency with Microsoft Word, Excel, and PowerPoint.
Technical – Preferred / Strong Plus
• Experience with RAVE EDC.
• Awareness or working knowledge of CDISC, CDASH, SDTM standards.
• Exposure to R, Python, or JavaScript and/or clinical data visualization tools/platforms.