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Remote Sas R Python Jobs in Oklahoma (NOW HIRING)

Data Analyst

Oklahoma City, OK · On-site +1

$100K - $110K/yr

Familiarity with statistical programming languages such as SAS, R, or Stata is helpful, but not ... Professional remote office environment. * Must be physically and mentally able to perform duties ...

Experience with Python, R, SQL, and advanced Excel * Experience with data modeling, predictive ... Ability to work independently in a self-starting, remote environment Required Education: * Bachelor ...

Experience with Python, R, SQL, and advanced Excel * Experience with data modeling, predictive ... Ability to work independently in a self-starting, remote environment Required Education: * Bachelor ...

Experience with Python, R, SQL, and advanced Excel * Experience with data modeling, predictive ... Ability to work independently in a self-starting, remote environment Required Education: * Bachelor ...

Senior Commercial Insurance Analyst - Remote

Kansas, OK · Remote

$70.10K - $92.80K/yr

Working knowledge of R or Python. * Experience with automating repetitive tasks. * Adaptability and ... Proficiency in Microsoft Office Suite, SAS, SQL, Visual Basic and various structured analysis and ...

Remote, United States Date Posted: May 5, 2026 Employment Type: Intern Job ID: R-1948 Description ... Modern programming languages such as JavaScript (NodeJS), C#, Java, or Python * Exposure to or ...

Remote, United States Date Posted: May 26, 2026 Employment Type: Full Time Job ID: R-1915 ... Excellent knowledge of Python and core data science and AI libraries including Pandas, NumPy ...

Remote, United States Date Posted: May 5, 2026 Employment Type: Intern Job ID: R-1950 Description ... Write basic automation scripts (Python or Bash) to support operational tasks * Assist with ...

Strong programming skills in Python, R, or similar analytical languages. * Extensive experience ... Strong mentoring and technical leadership capabilities. #LI-TS1 #remote Sedgwick is an Equal ...

Strong programming skills in Python, R, or similar analytical languages. * Extensive experience ... Strong mentoring and technical leadership capabilities. #LI-TS1 #remote Sedgwick is an Equal ...

Remote Sas R Python information

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

AspectRemote Sas R PythonRemote Data Analyst
Required SkillsSAS, R, Python, data manipulationExcel, SQL, data visualization, basic statistical analysis
CertificationsSAS certifications, R/Python proficiencyNone mandatory, often preferred certifications in Excel or SQL
Work EnvironmentData analysis, statistical modeling, programmingData interpretation, reporting, visualization
Industry UsageHealthcare, finance, pharmaceuticalsBusiness, marketing, finance

Remote Sas R Python roles focus on advanced statistical programming and data modeling using SAS, R, and Python, often in specialized industries. Remote Data Analysts handle data interpretation, reporting, and visualization, typically requiring skills in Excel and SQL. While both roles involve data work, Sas R Python positions demand programming expertise, whereas Data Analysts focus more on data presentation and insights.

What are the most commonly searched types of Sas R Python jobs in Oklahoma? The most popular types of Sas R Python jobs in Oklahoma are:
What are popular job titles related to Remote Sas R Python jobs in Oklahoma? For Remote Sas R Python jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Remote Sas R Python jobs in Oklahoma look for? The top searched job categories for Remote Sas R Python jobs in Oklahoma are:
What cities in Oklahoma are hiring for Remote Sas R Python jobs? Cities in Oklahoma with the most Remote Sas R Python job openings:
Data Engineer (remote option)

Data Engineer (remote option)

Vitaver & Associates, Inc.

Oklahoma City, OK • Remote

Other

Posted 26 days ago


Job description

14599 - Data Engineer (remote option) - Oklahoma City, OK
Start Date: ASAP
Type: Temporary Project
Estimated Duration: 6-12 months with possible extensions
Work Setting: remote option. Travel quarterly to office
Only candidates able to relocate as required should apply to avoid removal from future consideration.
Required:
  • Hands-on Data Engineering experience (5+ years);
  • Experience with SQL including correlated subqueries and window functions;
  • Experience with cloud platforms (GCP Big Query) including query performance optimization with partitioning strategies;
  • Experience with Python for data pipeline development, automation, and API integration including pandas, NumPy, and SQL Alchemy;
  • Experience with ETL transformation tools such as Azure Data Factory, GCP Dataproc, Dataflow, SSIS, and dbt;
  • Experience with orchestration tools;
  • Experience with REST APIs for data ingestion and system interoperability;
  • Experience with version control (Git);
  • Experience with R for statistical analysis and data manipulation;
  • Experience with Python ML Libraries.

Preferred:
  • Experience in a HIPAA-regulated environment with data privacy and security requirements;
  • Experience with standards-based health data exchange (HL7 v2/v3, FHIR);
  • Experience with cell suppression and statistical disclosure logic within SQL for public-facing health data outputs;
  • Experience with SAS;
  • Bachelor's degree in Computer Science, Engineering, Data Engineering, or related field.

Responsibilities include but are not limited to the following:
  • Design, implement, and maintain ELT/ETL pipelines across cloud platforms (Azure, GCP, AWS);
  • Architect and modernize data acquisition and ingestion pipelines for large-scale healthcare data;
  • Implement and manage data storage solutions (data lakes, warehouses) utilizing appropriate partitioning, security, and lifecycle policies;
  • Plan and execute data migrations across platforms including schema mapping, data validation, and cutover coordination;
  • Design and architect schemas to support migration of transactional database structures to data warehouse environments including dimensional modeling;
  • Evaluate and integrate new and emerging data sources, link datasets across systems, and develop processes to support novel data types;
  • Document data architectures, lineage, and standards and provide technical guidance and mentorship.