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Junior R Statistical Programmer Jobs in Oklahoma

TDW

Quality Assurance Engineer II

Tulsa, OK · On-site

The Quality Assurance Engineer is responsible to assist the Quality Manager to develop the quality ... Experience with statistical software such as Minitab, R or SAS. Knowledge, Skills, and Abilities

T D Williamson

Quality Assurance Engineer II

Tulsa, OK · On-site

The Quality Assurance Engineer is responsible to assist the Quality Manager to develop the quality ... Experience with statistical software such as Minitab, R or SAS. Knowledge, Skills, and Abilities

Badger Meter

Engineer II, Manufacturing

Tulsa, OK · On-site

$66K - $85K/yr

Utilize statistical tools (SPC, DOE, Gage R&R) to inform decision-making * Develop and maintain process documentation, work instructions, and procedures * Support engineering and capital projects

Badger Meter

Engineer II, Manufacturing

Tulsa, OK

$66K - $85K/yr

Utilize statistical tools (SPC, DOE, Gage R&R) to inform decision-making * Develop and maintain process documentation, work instructions, and procedures * Support engineering and capital projects

Pwc

Data Engineer - Manager

Tulsa, OK · On-site

$99K - $232K/yr

... junior staff. You are accountable for confirming project success and maintaining standards ... Statistics - Utilizing Amazon Web Services (AWS) and Azure Data Factory for data engineering ...

Pwc

Data Engineer - Manager

Oklahoma City, OK

$99K - $232K/yr

... junior staff. You are accountable for confirming project success and maintaining standards ... Statistics - Utilizing Amazon Web Services (AWS) and Azure Data Factory for data engineering ...

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Junior R Statistical Programmer information

What are typical challenges a Junior R Statistical Programmer might face when transitioning from academic projects to industry settings?

Junior R Statistical Programmers often find the shift from academic to industry work entails adapting to stricter timelines, code standardization, and collaborative workflows. In industry, you may need to follow specific documentation practices, utilize version control systems like Git, and adapt your code for scalability and reproducibility. Additionally, you’ll frequently collaborate with statisticians, data managers, and project leads, which requires strong communication skills and the ability to incorporate feedback from multiple stakeholders.

What is the difference between Junior R Statistical Programmer vs Data Analyst?

AspectJunior R Statistical ProgrammerData Analyst
Required SkillsProficiency in R, basic statistical knowledge, programming skillsData manipulation, visualization, statistical analysis, often using R or Excel
Work EnvironmentPharmaceutical or clinical research settings, working on data processing and reportingBusiness, marketing, or healthcare sectors analyzing large datasets for insights
CertificationsOften requires a degree in statistics, biostatistics, or related field; certifications like SAS or R preferred

While both roles involve data analysis and R programming, Junior R Statistical Programmers focus more on clinical or research data processing within regulated environments, whereas Data Analysts work across various industries analyzing business data. The roles share skills but differ in context and application.

What are the key skills and qualifications needed to thrive as a Junior R Statistical Programmer, and why are they important?

To thrive as a Junior R Statistical Programmer, you need a solid understanding of statistical concepts, programming proficiency in R, and a bachelor's degree in statistics, mathematics, computer science, or a related field. Familiarity with data management tools like SQL, version control systems such as Git, and statistical analysis packages in R is typically expected. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate with team members and clearly present analytical findings. These competencies ensure accurate data analysis, reproducible results, and successful teamwork within research or business environments.

What are Junior R Statistical Programmers?

Junior R Statistical Programmers are entry-level professionals who use the R programming language to analyze data, create statistical models, and generate reports, often for research, healthcare, or business purposes. They typically assist senior statisticians or data scientists by cleaning data, writing scripts, and performing basic statistical analyses. Their role helps organizations turn raw data into actionable insights, and they often work as part of a larger analytics or research team.
What are the most commonly searched types of R Statistical Programmer jobs in Oklahoma? The most popular types of R Statistical Programmer jobs in Oklahoma are:
What are popular job titles related to Junior R Statistical Programmer jobs in Oklahoma? For Junior R Statistical Programmer jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Junior R Statistical Programmer jobs in Oklahoma look for? The top searched job categories for Junior R Statistical Programmer jobs in Oklahoma are:
What cities in Oklahoma are hiring for Junior R Statistical Programmer jobs? Cities in Oklahoma with the most Junior R Statistical Programmer job openings:
Junior R Statistical Programmer jobs near you
Quality Assurance Engineer II

Quality Assurance Engineer II

TDW

Tulsa, OK • On-site

Full-time

Re-posted 4 days ago

Job description

At TDW we put people first - that means working everyday to ensure the pipelines that run through our communities are operating safely and reliably. What sets us apart is our expertise, experience and commitment.
Each day we dedicate ourselves to treating each other, our customers and our community with care and respect.
The Quality Assurance Engineer is responsible to assist the Quality Manager to develop the quality system in accordance with corporate policies, goals and objectives and the requirements of ISO 9001:2015, hence to contribute to improve the overall quality performance of the Company.
Key Responsibilities
Primary duties may include, but are not limited to:
  • Leads process and product improvement projects in the development of quality programs and procedures for TDW to ensure data collection is structured, managed, and utilized to benefit TDW's quality system.
  • Utilizes appropriate quality tools (e.g., problem solving and root cause analysis, lean and Sig Sigma) to help resolve issues related to non-conformances.
  • Supports the Material Review Board (MRB) to ensure that material is distributed appropriately and quickly.
  • Utilizes statistics, problem solving and other quality tools to monitor and improve TDW's business processes and to help troubleshoot production process and product issues.
  • Manages manufacturing related NCR/CAR (Non-Conformance Report / Corrective Action Request) activities to ensure timely administration of activities and records
  • Identifies and facilitate the resolution of problems at manufacturing sites
  • Provides regular reports detailing performance to key metrics including Cost of Failure
  • Designs any special testing requirements for evaluation of components or sub-assemblies that are manufactured.
  • Stays current on applicable weld regulations and reviews welding practices, inspections, and procedures to support compliance and continuous improvement.

Experience
  • Bachelor of Science degree in Statistics, Engineering, or other technical discipline preferred
  • 3 years Quality Engineering or Supplier Quality Engineering experience with an ISO 9001 certified company required, including experience supporting welding processes in a manufacturing environment.
  • Quality System Auditor certification (e.g., ASQ Certified Quality Auditor or RAB/QSA Certified Lead Auditor) preferred.
  • ASQ Certified Quality Engineer and/or Six Sigma certification preferred.
  • Experience with statistical DOE, SPC, ANOVA, Regression and Theory of Constraints.
  • Experience with statistical software such as Minitab, R or SAS.

Knowledge, Skills, and Abilities
  • Good understanding of Design Failure Mode Effect Analysis (DFMEA) and Process Failure Mode Effect Analysis (PFMEA).
  • Working knowledge of Advanced Product Quality Planning (APQP) tools preferred.
  • Working knowledge of Lean Manufacturing and Six Sigma Black Belt preferred.
  • Demonstrated ability to create, develop, organize and utilize complex databases in a quality environment.
  • Thorough understanding of advanced statistics and their application in an industrial environment.
  • Excellent written, verbal, presentation and multimedia communications skills.
  • Intermediate MS Office skills.
  • Ability to travel (internationally and domestically), up to 20% of the time.

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