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Sas R Python Internship Jobs in Durham, NC (NOW HIRING)

In-depth knowledge in practices, theories and methodologies associated with the professional discipline such as statistics, programming (such as Python, R, SAS, etc.), machine learning, model ...

... SAS Visual Analytics and Model Studio, is highly preferred. • Familiarity with Python, R, SQL, or other data programming languages. • Understanding of ethical AI, data privacy, and public sector ...

... Python, SAS, R, etc.) to create predictive analytics applications. 6. Use, maintain, share and collaborate through Truist internal code repositories to foster continual learning and cross-pollination ...

Quant Audit Manager

Raleigh, NC

$101.10K - $132.70K/yr

Strong knowledge of programming languages such as R, Python, or C++. * Strong knowledge of one or more database management tools such as SAS and/or SQL. * Strong analytical, facilitation ...

... as R, Python, or C++. 7. Strong knowledge of one or more database management tools such as SAS and/or SQL. 8. Strong analytical, facilitation, interpersonal and decision-making skills. 9. Strong ...

... SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions. • Review ...

Quant Audit Manager

Raleigh, NC

$101.10K - $132.70K/yr

... as R, Python, or C++. 6. Strong knowledge of one or more database management tools such as SAS and/or SQL. 7. Strong analytical, facilitation, interpersonal and decision-making skills. 8. Strong ...

Psychometric Analyst

Durham, NC · Remote

$70K - $80K/yr

Intermediate SAS programming skills * Experience with data workflow management, database management, and data visualization, preferred * Experience with R or Python, Quarto, and/or Rmarkdown ...

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Sas R Python Internship information

See Durham, NC salary details

$7

$52

$74

How much do sas r python internship jobs pay per hour?

As of May 31, 2026, the average hourly pay for sas r python internship in Durham, NC is $52.30, according to ZipRecruiter salary data. Most workers in this role earn between $48.80 and $57.84 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a SAS R Python Intern, and why are they important?

To thrive as a SAS R Python Intern, you need a solid understanding of statistics, data analysis, and programming fundamentals, often supported by coursework or a degree in a quantitative field. Familiarity with statistical software like SAS, R, and Python, as well as data visualization and database tools, is typically required. Strong problem-solving skills, attention to detail, and the ability to communicate technical findings clearly help interns stand out. These skills are crucial for successfully analyzing data, drawing actionable insights, and contributing effectively to data-driven projects within an organization.

What types of projects can I expect to work on during a SAS R Python internship, and how do these projects contribute to real business outcomes?

As a SAS R Python intern, you will typically work on data analysis, data cleaning, and developing predictive models using large datasets. Projects often involve collaborating with data scientists and business analysts to extract insights that drive decision-making, such as optimizing marketing campaigns or improving operational efficiency. These assignments allow you to apply statistical methods and programming skills in practical settings, directly supporting organizational goals. Interns also gain exposure to real-world data challenges and team-based problem-solving, making it a valuable stepping stone for future analytics roles.

What is a SAS R Python Internship?

A SAS R Python Internship is a temporary position designed for students or recent graduates to gain hands-on experience using statistical analysis and programming languages, specifically SAS, R, and Python. Interns typically work on data-driven projects, helping organizations analyze large datasets, develop predictive models, and automate data processes. This type of internship is common in industries like finance, healthcare, and tech, and is ideal for individuals interested in data science, analytics, or programming careers.

What is the difference between Sas R Python Internship vs Data Analyst Internship?

AspectSas R Python InternshipData Analyst Internship
Required SkillsKnowledge of SAS, R, Python, data manipulationProficiency in Excel, SQL, basic statistical analysis
Work EnvironmentData-focused, analytics teams, tech companiesBusiness units, consulting firms, finance
Industry UsageCommon in healthcare, finance, techWidespread across industries including marketing and finance

Both internships involve data analysis skills, but Sas R Python Internships focus more on programming and statistical tools, while Data Analyst Internships emphasize business insights and reporting. The choice depends on whether you prefer technical programming or business-oriented analysis.

Business Analyst/PM - Clinical Data

Business Analyst/PM - Clinical Data

Tanisha Systems

Morrisville, NC

Other

Posted 29 days ago


Job description

Business Analyst/PM - Clinical Data Morrisville, NC 27560 - Onsite Role - Prefer local candidates Salary Market (DOE) FTE role We are looking for a seasoned Business Analyst with experience in requirement analysis and delivery of data & analytics solutions for regulated industries (Life Sciences / Pharma). The ideal candidate will drive requirement gathering, compliance alignment, and stakeholder engagement for a GxP-compliant, cloud-native data platform on Microsoft Fabric and Azure. Success will be measured by the ability to translate CDM/Biostatistics needs into validated pipelines, dashboards, and audit-ready documentation.

The Business Analyst acts as the bridge between clinical stakeholders and technical teams, ensuring requirements are captured, translated, and delivered effectively. Leads requirement gathering & documentation across CDM, Biostatistics, and vendor partners. Translates business and regulatory needs into functional specifications aligned with 21 CFR Part 11, GxP, and HIPAA.

Supports validation frameworks, audit-ready documentation, and reporting requirements such as Power BI dashboards and compliance scorecards. Facilitates workshops, UAT sessions, and milestone signoffs to secure stakeholder alignment. Prepares for future readiness, advanced analytics, and AI-driven insights.

Skills / Experience 10+ years in IT with 6+ years in Business Analysis for regulated environments (Life Sciences, Pharma, Healthcare, Clinical Data Management, Biostatistics). Proven ability to gather, document, and validate requirements; conduct workshops; create functional specifications; ensure compliance with FDA 21 CFR Part 11, GxP, HIPAA Knowledge of regulatory frameworks including 21 CFR Part 11, GxP, HIPAA, GDPR; experienced in IQ/OQ/PQ documentation, SOPs, and audit-ready deliverables Strong domain knowledge in CDM, Biostatistics workflows, CDISC (SDTM/ADaM), FDA eCTD; Tools: GitHub Projects, DevOps board, Jira, Power BI, Microsoft Fabric Understanding of Microsoft Fabric, governance policies, compliance documentation; exposure to BI solutions using Power BI Exposure to CDISC/SDTM/ADaM standards, OMOP mapping, advanced analytics (R, Python, SAS), and AI-driven accelerators (WinAIDM) Skilled in stakeholder engagement, workshops, UAT sessions, and cross-functional collaboration Experience defining validation rules, monitoring dashboards, and exception handling processes Experience leveraging GenAI tools (GitHub Copilot, Microsoft Fabric Copilot, M365 Copilot) Bachelor s degree in Life Sciences, Computer Science, or related field Role / Job Description Requirements Analysis & Translation Lead requirement gathering sessions; translate regulatory and business needs into functional specifications; document user stories, acceptance criteria, and workflows; author BRD and FRS Data Governance & Compliance Define validation rules; ensure dataset versioning, lineage, audit trails, and electronic signatures; collaborate with QA teams for validation documentation and SOPs; support compliance reviews and inspection readiness Analytics & Reporting Enablement Capture reporting requirements for Power BI dashboards, compliance scorecards, and study progress reports; define business rules for secure analytics environments; ensure reporting aligns with governance and audit workflows Stakeholder Engagement & Delivery Facilitate workshops, UAT sessions, and requirement walkthroughs; act as liaison between business stakeholders and technical teams; drive milestone sign-offs for requirement validation and compliance readiness Operational Oversight & Vendor Collaboration Define secure vendor data exchange requirements; monitor data quality dashboards; coordinate issue resolution; ensure scalability and performance benchmarks Future Readiness Contribute to roadmap planning for CDISC/SDTM/ADaM integration, OMOP mapping, advanced analytics, and AI-driven insights Communication & Troubleshooting Build productive relationships across teams; provide feedback during workshops; troubleshoot requirement gaps, compliance risks, and process inefficiencies; work in Agile/Scrum projects with Jira or Azure DevOps Secondary Skills / Good to Have Life Sciences domain knowledge, deeper knowledge of clinical data flows, CDISC standards, regulatory submission processes, vendor data exchange practices Advanced Analytics & AI Exposure Awareness of AI-driven accelerators (WinAIDM, Fabric Copilot); exposure to RWE and predictive modeling in clinical trials Certifications / Good to Have CBAP, PMI-PBA, IIBA; Microsoft certifications (DP-600, DP-203) Expected Outcomes Phase 1 Clinical Data Repository delivered within 16 18 weeks; requirements translated into compliant workflows and validated pipelines; audit-ready documentation completed. Power BI dashboards and compliance scorecards actively used by stakeholders; improved collaboration across CDM, Biostatistics, IT, and vendors; foundation established for Phase 2 (CDISC/OMOP integration, advanced analytics, AI-driven insights).

This Role Matters Ensures regulatory confidence by embedding compliance into every requirement; Drives operational efficiency by reducing manual data transfers and enabling secure vendor collaboration Enables analytics readiness by defining requirements for dashboards, scorecards, and validated pipelines; Fosters stakeholder alignment through workshops, UAT sessions, and milestone signoffs Lays the foundation for innovation, preparing the organization for CDISC/OMOP integration, advanced analytics, and AI-driven insights