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Entry Level Statistical Programmer Jobs (NOW HIRING)

Augur Consulting

Entry-Level Analyst

Arlington, VA · On-site

Entry-Level Analyst U.S. citizenship required. Are you a critical thinker with acumen for problem ... Statistics, Finance, Business, Physics, Engineering, etc.) Requirements: Candidates must be ...

SynergisticIT

junior software programmer fullstack

Seattle, WA · On-site

$76K - $99K/yr

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python ... Recent grads in CS, Engineering, Math, or Statistics with limited or no job experience Jobseekers ...

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Entry Level Statistical Programmer information

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$84.5K

$147.3K

$249K

How much do entry level statistical programmer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for entry level statistical programmer in the United States is $147,292.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,000.00 and $160,000.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Statistical Programmer vs Data Analyst?

AspectEntry Level Statistical ProgrammerData Analyst
Required CredentialsBachelor's in Statistics, Biostatistics, or related field; basic programming skills (SAS, R)Bachelor's in Statistics, Data Science, or related field; proficiency in Excel, SQL, and visualization tools
Work EnvironmentPharmaceutical or clinical research settings; focus on data processing and programmingVarious industries including finance, marketing, healthcare; focus on data interpretation and reporting
Employer & Industry UsagePharmaceutical companies, CROs, biotech firmsCorporations, consulting firms, healthcare organizations

While both roles involve working with data, Entry Level Statistical Programmers primarily focus on programming and data management within clinical or research settings, whereas Data Analysts interpret data to inform business decisions across various industries.

What does an Entry Level Statistical Programmer do?

An Entry Level Statistical Programmer assists in analyzing data using statistical software, such as SAS or R, primarily in industries like pharmaceuticals, healthcare, or research. They are responsible for coding, cleaning, and organizing datasets, generating tables, listings, and figures, and ensuring data accuracy. These programmers work closely with statisticians and data managers to support clinical trials or research projects. The role serves as a foundation for more advanced programming and data analysis positions.

What are the key skills and qualifications needed to thrive as an Entry Level Statistical Programmer, and why are they important?

To thrive as an Entry Level Statistical Programmer, you need a solid understanding of statistics, programming (especially in SAS, R, or Python), and a relevant degree such as in statistics, mathematics, or computer science. Familiarity with data analysis tools, statistical software (like SAS or R), and version control systems is typically required, and SAS certification can be an advantage. Attention to detail, problem-solving ability, and effective communication are valuable soft skills for this role. These skills and qualities are crucial for accurate data analysis, efficient collaboration, and producing reliable results in data-driven environments.

What are some common challenges faced by entry level statistical programmers when transitioning from academic projects to real-world clinical trial data?

Entry level statistical programmers often find the transition to industry challenging due to the complexity of real-world clinical trial data, strict regulatory requirements, and the need to adhere to standardized processes like CDISC. Unlike academic projects, the work environment emphasizes collaboration with statisticians, data managers, and clinical teams, making communication and teamwork vital. Additionally, maintaining high-quality documentation and learning to use industry-specific tools and programming standards are crucial for success. Seeking mentorship and being proactive in learning these processes can help new programmers adapt more quickly.
More about Entry Level Statistical Programmer jobs
What cities are hiring for Entry Level Statistical Programmer jobs? Cities with the most Entry Level Statistical Programmer job openings:
What are the most commonly searched types of Statistical Programmer jobs? The most popular types of Statistical Programmer jobs are:
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What job categories do people searching Entry Level Statistical Programmer jobs look for? The top searched job categories for Entry Level Statistical Programmer jobs are:
Entry Level Statistical Programmer jobs near you
Infographic showing various Entry Level Statistical Programmer job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 86% Full Time, 12% Part Time, and 1% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $147,292 per year, or $70.8 per hour.
Analytics Engineer I (Entry-Level) (3897)

Analytics Engineer I (Entry-Level) (3897)

Navarro Inc.

Oak Ridge, TN • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago

Job description

Navarro Research and Engineering is recruiting an Analytics Engineer I (Entry-Level) (3897) in Oak Ridge, TN.
Navarro Research & Engineering is an award-winning federal contractor dedicated to partnering with clients to advance clean energy and deliver effective solutions for complex challenges in the nuclear and environmental fields. Joining Navarro means being a part of an exceptional team committed to quality and safety while also looking for innovative strategies to create value for the client's success. Headquartered in Oak Ridge, Tennessee, Navarro has active programs in place across the nation for DOE/NNSA, NASA, and the Department of Defense.
Position Summary
The Analytics Engineer I (Entry-Level) will support Navarro's Data & Analytics team by helping build and maintain data pipelines, assisting with reporting and dashboarding efforts, and contributing to applied AI projects. This role is well suited for an early-career professional interested in growing into a strong analytics or applied AI contributor, including work involving AI/ML techniques to extract, structure, and validate key information from unstructured documents.
Responsibilities
  • Assist in designing, building, and maintaining data pipelines and ETL/ELT processes.
  • Write and optimize SQL queries to extract, transform, and analyze data from multiple sources.
  • Support the development of dashboards and reports using Excel and other business intelligence tools.
  • Use Python and/or R to automate data workflows, clean datasets, and perform exploratory analysis.
  • Build and support AI/ML-driven workflows for extracting key text and structured data from documents, including NLP, LLM-based extraction, and OCR plus ML pipelines.
  • Collaborate with data scientists, analysts, and business stakeholders to understand data and applied AI project needs.
  • Help document data models, pipeline logic, and AI/ML workflow processes.
  • Contribute to data quality checks and validation processes for both traditional data and AI-generated outputs.

Requirements
Requirements
  • Bachelor's degree in Data Analytics, Statistics, Computer Science, Mathematics, Engineering, or a related field.
  • Working knowledge of SQL for querying and manipulating data.
  • Proficiency in Excel, including formulas, pivot tables, and data visualization.
  • Proficiency in Python and/or R, including experience with relevant ML/AI libraries such as pandas, scikit-learn, or similar tools.
  • Hands-on exposure to AI/ML concepts through coursework, projects, or internships, such as text extraction, natural language processing, or document processing.
  • Strong analytical and problem-solving skills.
  • Good communication skills and the ability to work in a collaborative, cross-functional environment.
  • Attention to detail and a commitment to data accuracy.

Preferred Qualifications
  • Master's degree in a relevant quantitative field.
  • Experience with cloud platforms such as Azure, AWS, or Google Cloud and BI tools such as Tableau, Power BI, or Looker.
  • Familiarity with version control, such as Git, and basic software engineering practices.
  • Experience with LLM-based tools or APIs for document parsing, text extraction, entity recognition, or information extraction.
  • Experience with OCR tools or unstructured document processing, including PDF or text parsing libraries
  • Local candidates are preferred.

Due to the nature of the government contract requirements and/or clearances requirements, US citizenship is required.
Navarro is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, race, religion, color, national origin, age, disability, veteran's status, or any classification protected by applicable state or local law.
EEO Employer/Vet/Disabled
Benefits
  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation & Public Holidays)
  • Short Term & Long Term Disability

Apply