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Afternoon Data Analyst R Programming Jobs in Morrisville, MO

Brightli

Principal AI Engineer

Springfield, MO · On-site

The Principal AI Engineer is the senior technical contributor within Analytics responsible for designing, developing, and implementing enterprise AI capabilities on the data platform with a focus on ...

Brightli

Principal AI Engineer

Springfield, MO · On-site

The Principal AI Engineer is the senior technical contributor within Analytics responsible for designing, developing, and implementing enterprise AI capabilities on the data platform with a focus on ...

Brightli

Principal AI Engineer

Springfield, MO · On-site

As the senior AI technical contributor within Analytics, you'll partner with Data Engineering and Analytics teams to set architectural patterns, best practices, and governance-aligned standards for ...

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All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Morrisville, MO

Afternoon Data Analyst R Programming information

See Morrisville, MO salary details

$32.2K

$78.2K

$128.7K

How much do afternoon data analyst r programming jobs pay per year?

As of Sep 3, 2026, the average yearly pay for afternoon data analyst r programming in Morrisville, MO is $78,208.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,100.00 and $91,800.00 per year, depending on experience, location, and employer.

What is an afternoon data analyst r programming?

An Afternoon Data Analyst specializing in R Programming is a data professional who primarily works afternoon shifts and uses the R programming language to analyze, interpret, and visualize data. Their responsibilities typically include cleaning data, performing statistical analyses, and generating reports to support business decisions. They may work across various industries, collaborating with teams to provide insights and automate data processes using R. Afternoon shifts can be ideal for organizations that operate globally or require data support outside standard business hours. Proficiency in R, statistical techniques, and data visualization tools are essential skills for this role.

What are the key skills and qualifications needed to thrive as an afternoon data analyst specializing in R programming?

To thrive as an Afternoon Data Analyst specializing in R Programming, you need a strong background in statistics, data analysis, and proficiency with R, often supported by a degree in a quantitative field. Experience with data visualization tools, R packages (like tidyverse), and familiarity with databases or version control systems (such as Git) is typically required. Critical thinking, attention to detail, and effective communication are essential soft skills for interpreting results and presenting insights to stakeholders. These skills ensure accurate data-driven decisions, efficient workflow, and the ability to translate complex data into actionable business strategies.

What are some common challenges faced by afternoon data analysts working with R programming, and how can they be addressed?

Afternoon Data Analysts using R Programming often encounter challenges such as handling large datasets efficiently, ensuring code reproducibility, and collaborating with team members across different shifts. To address these, it's helpful to utilize R packages designed for big data (like data.table or dplyr), maintain clear and well-documented scripts, and use version control systems like Git for seamless collaboration. Regular communication with team members during shift handovers and leveraging collaborative tools can also enhance workflow and reduce misunderstandings.

What is the difference between Afternoon Data Analyst R Programming vs Morning Data Analyst R Programming?

AspectAfternoon Data Analyst R ProgrammingMorning Data Analyst R Programming
Required CredentialsBachelor's in Data Science, Statistics, or related field; R programming skillsBachelor's in Data Science, Statistics, or related field; R programming skills
Work EnvironmentTypically in office settings, working during afternoon hoursOffice environment, working during morning hours
Employer & Industry UsageUsed in industries with shift-based operations like finance, healthcareCommon in similar industries, often with flexible scheduling
Search & Comparison IntentPeople comparing different shift roles or schedules in data analysisSimilar search intent focusing on shift timing differences

The main difference between Afternoon Data Analyst R Programming and Morning Data Analyst R Programming lies in their work hours. Both roles require similar skills, credentials, and are used in comparable industries. The choice depends on personal schedule preferences and employer shift structures.

What cities near Morrisville, MO are hiring for Afternoon Data Analyst R Programming jobs?

Cities near Morrisville, MO with the most Afternoon Data Analyst R Programming job openings:

Afternoon Data Analyst R Programming jobs near you

Product Analyst I- Catalog Content

O'Reilly Auto Parts

Springfield, MO • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago

Key responsibilities

  • Support the lifecycle management of catalog content, including vendor data intake, publication, and retirement.

  • Monitor and triage issues related to data ingestion pipelines, catalog feed errors, and data quality problems.

  • Collect, analyze, and interpret catalog usage data to identify gaps and support improvements.

O'Reilly Auto Parts rating

5.3

Company rating: 5.3 out of 10

Based on 1,905 frontline employees who took The Breakroom Quiz

557th of 739 rated retailers

Job description

The Product Analyst I supports the lifecycle management of catalog content, from vendor data intake through publication and retirement of listings. This role uses data to understand how technicians, retailers, and end consumers in both the DIY and DIFM segments search for and select parts, and works closely with catalog business stakeholders, engineering, and vendor management to ensure the catalog is accurate, complete, and easy to shop against fitment (year/make/model/engine) attributes.
This is an on-site position is located in Springfield, MO. Remote work is not an option for this position.
Responsibilities and Duties:
  • Monitor the health of the parts catalog across its lifecycle, including new vendor onboarding, seasonal item refreshes, and end-of-life/discontinued part retirement.
  • Collaborate with Product Owners and catalog business stakeholders to define requirements for catalog structure, attribute taxonomy, fitment logic, and category prioritization.
  • Support ingestion of supplier and OEM/aftermarket catalog data (ACES/PIES feeds, vendor spreadsheets, API feeds) - validating file formats, mapping fields, and flagging malformed or incomplete records before they reach production.
  • Monitor data ingestion pipelines for catalog feeds, triaging failed loads, duplicate items, mismatched fitment data, and pricing or inventory sync errors, and escalating recurring issues to engineering.
  • Support testing and reporting on AI initiatives applied to catalog data ingestion and publication (e.g., automated attribute mapping, fitment matching, and content generation), documenting accuracy, exceptions, and areas needing human review.
  • Assist in the design and execution of A/B tests and other experiments to evaluate the impact of catalog changes such as search relevance tuning, filter/facet layout, and fitment-widget improvements.
  • Collect, analyze, and interpret catalog usage data - search terms, zero-result queries, fitment lookup abandonment, and part-page conversion - to uncover gaps in coverage or attribute quality.
  • Plan and execute User Acceptance Testing (UAT) for catalog releases, including writing test cases against fitment accuracy, attribute completeness, image/spec display, and cross-reference (interchange) data prior to go-live.
  • Coordinate UAT sign-off with catalog business stakeholders, QA, and vendor management, documenting defects, tracking resolution, and confirming fixes before production release.
  • Gather and synthesize feedback from end users across the DIY and DIFM segments (technicians, counter staff, and retail/DIY customers) through support tickets, surveys, and usability sessions to identify pain points in part search, fitment selection, and catalog navigation.
  • Support market research and competitive analysis of automotive catalog and fitment platforms to benchmark data coverage, search experience, and vendor integration practices.
  • Support the rollout of new catalog features and vendor integrations by executing assigned tasks in the project/development plan.
  • Contribute to recurring data quality and analytics reports covering catalog completeness, fitment accuracy rates, ingestion error trends, and UAT defect metrics.
  • Present data-driven recommendations on catalog data quality, ingestion process improvements, and user feedback themes to product, engineering, and design teams.
  • Provide guidance and troubleshooting support to internal users and clients on catalog capabilities, fitment tools, and data submission requirements, ensuring the technical and business context of the catalog is well understood.
  • Work within an established project management plan to achieve catalog release and data quality goals.
  • Demonstrate catalog features and fitment tools to internal stakeholders and clients, including detailed walkthroughs on request.
  • Develop own capabilities through training on catalog data standards (e.g., ACES/PIES), automotive fitment concepts, and industry best practices, including relevant conferences and specialist media.

Skills:
Required:
  • Manages and develops all aspects of a product or catalog dataset to ensure it achieves its full impact and value in the market.
  • Oversees and manages all stages of a catalog product's lifecycle, from vendor data intake to retirement, ensuring efficient ingestion processes, timely publication, and adherence to data quality standards.
  • Plans, organizes, prioritizes, and oversees catalog data and UAT activities to efficiently meet release objectives.
  • Communicates and articulates data quality issues, ingestion errors, and potential resolutions in a clear, compelling, and tailored manner to address specific stakeholder needs.
  • Analyzes and researches automotive aftermarket and OEM market conditions to develop a comprehensive understanding of fitment and catalog trends that benefit the organization.
  • Determines and analyzes trends from catalog usage and ingestion data to compile reports that support data quality and product decisions.
  • Identifies potential stakeholders (vendors, catalog business stakeholders, engineering, end users), analyzes their expectations, and develops strategies for managing them through the release cycle.
  • Reviews and evaluates catalog data requirements and UAT findings to develop appropriate remediation plans or release actions.
  • Tests and evaluates the performance of AI-driven tools used in catalog data ingestion and publication, documenting results and recommending adjustments to improve accuracy and reliability.
  • Identifies, sequences, and resources catalog release and UAT schedules for timely completion.
  • Plans, identifies, monitors, analyzes, and prioritizes risks in data ingestion and catalog releases (e.g., feed failures, fitment errors), creating response plans and managing risk if it occurs.
  • Identifies, verifies, and manages changes to catalog scope (new vendors, categories, attribute sets), utilizing the most appropriate approach.
  • Identifies appropriate measures for assessing catalog data quality and fitment accuracy, validates with key stakeholders, and collects performance measures to recommend actions that increase catalog value.
  • Identifies, tracks, and enables the achievement of planned benefits and outcomes from catalog and data ingestion initiatives.
  • Develops an effective change strategy based on gap analyses of catalog data quality and readiness assessments, including transition states and release plans.

Education: Associate's Degree or equivalent technical training/certification
Experience: Sound experience and understanding of straightforward procedures or systems (7 to 12 months)
Managerial Experience: Basic experience of coordinating the work of others (4 to 6 months)
O'Reilly Auto Parts has a proven track record of growth and stability. O'Reilly is full of successful career stories and believes in a strong promote-from-within philosophy, encouraging you to grow your career along with the organization.
Total Compensation Package:
  • Competitive Wages & Paid Time Off
  • Stock Purchase Plan & 401k with Employer Contributions Starting Day One
  • Medical, Dental, & Vision Insurance with Optional Flexible Spending Account (FSA)
  • Team Member Health/Wellbeing Programs
  • Tuition Educational Assistance Programs
  • Opportunities for Career Growth

O'Reilly Auto Parts is an equal opportunity employer. The Company does not discriminate on the basis of race, religion, color, national origin or ancestry (including immigration status or citizenship), sex, sexual orientation, gender identity, pregnancy (including childbirth, lactation, and related medical conditions,) age (40 and over), veteran status, uniformed service member status, physical or mental disability, genetic information (including testing or characteristics) or another protected status as defined by local, state, or federal law, as applicable.
Qualified individuals with a disability may be entitled to reasonable accommodation under the Americans with Disabilities Act. If you require a reasonable accommodation during the application or employment process, please send an email to: rar@oreillyauto.com or call (800) 471-7431 option , and provide your requested accommodation, and position details.

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