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Afternoon Data Analyst R Programming Jobs in Modesto, CA

PGD Reliability Engineer

Tracy, CA ยท On-site

$92K - $138K/yr

This position requires analyzing performance data to direct operational teams toward units ... The engineer manages event response processes, ensures proper service request documentation, and ...

Continuous Improvement Engineer

Stockton, CA ยท On-site

$78K - $90K/yr

Continuous Improvement Engineer We are seeking a high-energy, results-driven, and detail-oriented ... Skilled in data analytics and project tracking tools (Excel, Power BI, MS Projects, Etc.

Continuous Improvement Engineer We are seeking a high-energy, results-driven, and detail-oriented ... Skilled in data analytics and project tracking tools (Excel, Power BI, MS Projects, Etc.

Continuous Improvement Engineer We are seeking a high-energy, results-driven, and detail-oriented ... Skilled in data analytics and project tracking tools (Excel, Power BI, MS Projects, Etc.

Senior Industrial Engineer

Lathrop, CA ยท On-site

$102K - $135K/yr

This will include process engineering, data collection and analysis, associate training, as well as implementation and support of the program. The successful candidate will provide support for all DC ...

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Afternoon Data Analyst R Programming information

See Modesto, CA salary details

$35.9K

$87.2K

$143.5K

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

As of Jun 15, 2026, the average yearly pay for afternoon data analyst r programming in Modesto, CA is $87,186.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,900.00 and $102,300.00 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 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 are the key skills and qualifications needed to thrive as an Afternoon Data Analyst specializing in R Programming, and why are they important?

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 the most commonly searched types of Data Analyst R Programming jobs in Modesto, CA? The most popular types of Data Analyst R Programming jobs in Modesto, CA are:
What are popular job titles related to Afternoon Data Analyst R Programming jobs in Modesto, CA? For Afternoon Data Analyst R Programming jobs in Modesto, CA, the most frequently searched job titles are:
What job categories do people searching Afternoon Data Analyst R Programming jobs in Modesto, CA look for? The top searched job categories for Afternoon Data Analyst R Programming jobs in Modesto, CA are:
What cities near Modesto, CA are hiring for Afternoon Data Analyst R Programming jobs? Cities near Modesto, CA with the most Afternoon Data Analyst R Programming job openings:
Data Scientist - Predictive Analytics, Senior

Data Scientist - Predictive Analytics, Senior

PG&E Corporation

Modesto, CA โ€ข Hybrid

Full-time

Posted 12 hours ago


Job description

Requisition IDย # 167320ย 

Job Category: Accounting / Financeย 

Job Level: Individual Contributor

Business Unit: Electric Engineering

Work Type: Hybrid

Job Location: Oakland; Alameda; Alta; American Canyon; Angels Camp; Antioch; Auberry; Auburn; Avenal; Avila Beach; Bakersfield; Balch Camp; Bay Point; Bear Valley; Belden; Bellota; Belmont; Benicia; Berkeley; Brentwood; Brisbane; Buellton; Burney; Buttonwillow; Calistoga; Campbell; Canyon Dam; Canyondam; Capitola; Caruthers; Chico; Clearlake; Clovis; Coalinga; Colusa; Concord; Concord; Corcoran; Cottonwood; Cupertino; Daly City; Danville; Davis; Dinuba; Downieville; Dublin; Emeryville; Eureka; Fairfield; Folsom; Fort Bragg; Fortuna; Fremont; French Camp; Fresno; Fresno; Fulton; Garberville; Geyserville; Gilroy; Goodyear; Grass Valley; Guerneville; Half Moon Bay; Hayward; Hinkley; Hollister; Holt; Houston; Huron; Jackson; Kerman; King City; Lakeport; Lemoore; Lincoln; Linden; Livermore; Lodi; Loomis; Los Banos; Lower Lake; Madera; Magalia; Manteca; Manton; Mariposa; Martell; Marysville; Maxwell; Menlo Park; Merced; Meridian; Millbrae; Milpitas; Modesto; Monterey; Montgomery Creek; Morgan Hill; Morro Bay; Moss Landing; Mountain View; Napa; Needles; Newark; Newman; Novato; Oakdale; Oakhurst; Oakley; Olema; Orinda; Orland; Oroville; Palo Alto; Palo Cedro; Paradise; Parkwood; Paso Robles; Petaluma; Pioneer; Pismo Beach; Pittsburg; Placerville; Pleasant Hill; Point Arena; Potter Valley; Quincy; Rancho Cordova; Red Bluff; Redding; Richmond; Ridgecrest; Rio Vista; Rocklin; Roseville; Round Mountain; Sacramento; Salida; Salinas; San Bruno; San Carlos; San Francisco; San Francisco; San Jose; San Luis Obispo; San Mateo; San Rafael; San Ramon; San Ramon; Sanger; Santa Cruz; Santa Maria; Santa Nella; Santa Rosa; Selma; Shaver Lake; Sonoma; Sonora; South San Francisco; Springville; Stockton; Storrie; Taft; Tracy; Turlock; Twain; Ukiah; Vacaville; Vallejo; Walnut Creek; Wasco; Watsonville; West Sacramento; Wheatland; Whitmore; Willits; Willow Creek; Willows; Windsor; Winters; Woodland; Yuba City

Department Overview

The System Performance, Reliability and Resiliency Strategy team within the overall Electric Transmission and Distribution Engineering organization is responsible for planning, organizing, and managing the resources necessary to successfully execute PG&Eโ€™s Electric Reliability Strategy and initiatives. This team of forwardโ€“thinking individuals will be tasked with deploying technology and infrastructure and influencing the organization to achieve the companyโ€™s reliability goals. The team is responsible for implementing programs required to modernize the electric grid allowing for safe, resilient and efficient operations. The team participates in a cross functional team of internal and consulting participants being tasked with leading the transition of a project from development and testing to being operational for each phase of each project.

Position Summary

Within the System Performance, Reliability and Resiliency Strategy team, this position reports to the Senior Manager of Reliability Analytics and is responsible for developing advanced data science models and industry-leading anomaly detection techniques to identify potential failures and enhance the reliability of the electric transmission and distribution grid.ย 

Key responsibilities include designing, developing, and executing scripts, programs, models, algorithms, and processes using structured and unstructured data from diverse sources and of varying sizes. The goal is to generate defensible, valid, scalable, reproducible, and well-documented machine learning and artificial intelligence models (predictive or optimization) to support problem-solving and strategic decision-making.

The role also involves active participation in internal and external communities of practice in data science, AI, and machine learning to stay current and contribute to advancements in the field. Additionally, the candidate will help educate non-technical stakeholders on the benefits, limitations, and maturity of data science solutions.

In this role, the successful candidate will be uniquely positioned at the forefront of utility industry analytics. Working as part of cross-functional teams, including data engineers, data scientists, technologists, and subject matter experts โ€“ this individual will lead the development of data science capabilities that could lead to paradigm changes in how the utility operates.

  • This position is hybrid, working from your remote office and your assigned work location based on business need. The assigned work location will be within the PG&E Service Territory.

PG&E is providing the salary range that can reasonably be expected for this position at the time of theย job posting. This salary range is specific to the locality of the job. The actual salary paid to an individual will beย based on multiple factors, including, but not limited to, internal equity, specific skills, education, licenses or certifications, experience,ย market value, and geographic location.ย The decision will be made on a case-by-case basis related to these factors. This job is also eligible to participate in PG&Eโ€™s discretionary incentive compensation programs.ย ย 

Bay Area -ย  $126,000 - 179,300

&/OR

California: $120,000 - 170,500

Job Responsibilities

  • Lead research and development of state-of-the-art methodologies to detect potential system failures and improve the reliability of the electric transmission and distribution grid.
  • Applies data science/ machine learning /artificial intelligence methods to develop scalable, defensible and reproducible models,ย 
  • Serves as the technical lead for the development of predictive/reliability analytics models.
  • Develops python codes for data processing and data science model developments (e.g., ML/AI models, advanced statistical models)
  • Documents datasets, modeling processes, and result to ensure transparency, reproducibility, and defensibility.ย 
  • Contribute to the development of data science strategies aligned with system performance, reliability, and resiliency team goals.
  • Communicate technical concepts and model results to internal/external stakeholders.ย 

Qualifications

Minimum:

  • Bachelorโ€™s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field
  • 4 years in data science OR 2 years, if possess Masterโ€™s Degree, as described above

Desired:

  • Ph.D. or Masterโ€™s degree in Electrical Engineering, Mechanical Engineering, Operations Research, Transportation Engineering, Physics, Applied Sciences, Statistics, or a related field.ย 
  • Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
  • Strong foundation in statistics, machine learning (ML), and artificial intelligence (AI).
  • Hands-on and theoretical experience in developing and deploying data science and ML models using Python.
  • Proven ability to formulate and solve unstructured, complex problems using data-driven approaches.
  • Proficiency in working with large datasets, including structured and unstructured data from diverse sources.
  • Excellent communication skills, with the ability to explain technical concepts to non-technical audiences.
  • Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies