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Entry Data Scientist Jobs (NOW HIRING)

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

... entry point of the range, the decision will be made on a case-by-case basis related to these ... Applies data science/ machine learning /artificial intelligence methods to develop defensible and ...

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Entry Data Scientist information

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$46K

$165K

$243.5K

How much do entry data scientist jobs pay per year?

As of Jul 17, 2026, the average yearly pay for entry data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are Entry Data Scientists?

Entry Data Scientists are professionals at the beginning of their data science careers who use statistical analysis, programming, and data visualization to extract meaningful insights from data. They typically work with large datasets, clean and preprocess data, build and test models, and help solve business problems using data-driven approaches. Entry-level data scientists often collaborate with more experienced data scientists, engineers, and business stakeholders to support projects and improve decision-making processes. They usually have foundational knowledge in mathematics, statistics, and programming languages like Python or R.

What are the key skills and qualifications needed to thrive as an Entry Data Scientist, and why are they important?

To thrive as an Entry Data Scientist, you need a solid grasp of statistics, data analysis, and programming languages like Python or R, typically supported by a degree in a quantitative field. Familiarity with tools such as SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and data visualization platforms is highly valuable. Strong problem-solving abilities, curiosity, and effective communication skills set successful candidates apart in this role. These competencies enable you to extract actionable insights from data and collaborate effectively with technical and non-technical stakeholders.

What is the difference between Entry Data Scientist vs Data Analyst?

AspectEntry Data ScientistData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Math, Statistics, or related field; strong Excel and data visualization skills
Work EnvironmentCollaborates with data science teams, develops models, and explores dataPrepares reports, interprets data, and supports decision-making
Industry UsageUsed in tech, finance, healthcare, and more for predictive modelingCommon across marketing, finance, and operations for reporting and analysis

Entry Data Scientists focus on building models and applying machine learning techniques, often requiring programming skills. Data Analysts primarily interpret data, create reports, and support business decisions. While both roles work with data, Entry Data Scientists tend to handle more technical tasks involving modeling, whereas Data Analysts focus on data interpretation and visualization.

What types of projects and responsibilities can an entry-level data scientist expect in their first year?

As an entry-level data scientist, you'll typically work on tasks such as cleaning and preprocessing data, building simple predictive models, and assisting with data visualization for reporting. You may collaborate closely with more experienced data scientists, data engineers, and business analysts to help frame business problems into analytical solutions. It's common to contribute to parts of larger projects, such as supporting feature engineering or testing model performance, while learning best practices in coding and data analysis. Over time, you may be given ownership of small projects, which helps build your expertise and prepares you for more complex assignments.
More about Entry Data Scientist jobs
What cities are hiring for Entry Data Scientist jobs? Cities with the most Entry Data Scientist job openings:
What states have the most Entry Data Scientist jobs? States with the most job openings for Entry Data Scientist jobs include:
Infographic showing various Entry Data Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Data Scientist, Expert

Data Scientist, Expert

PG&E Corporation

Berkeley, CA โ€ข Hybrid

Full-time

Posted 10 days ago


Job description

Requisition ID # 173213 

Job Category: Information Technology 

Job Level: Individual Contributor

Business Unit: Energy Delivery

Work Type: Hybrid

Job Location: San Ramon; 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; 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; Oakland; Oakley; Olema; Orinda; Orland; Oroville; Palo Alto; Palo Cedro; Paradise; Parkwood; Paso Robles; Petaluma; Pioneer; Pismo Beach; Pittsburg; Placerville; Pleasant Hill; Pleasanton; 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; 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

Applied Technology Services (ATS) has been providing technology-based, innovative, high-value services to the company for over 50 years. ATS is a multidisciplinary team of over 130 engineers, scientists, and technicians. The ATS vision is to be a forward-thinking, technological leader providing high-value solutions and services needed across the Company. ATS high value services also help proactively avoid future problems by specifying equipment, materials and methods that are best practices in the industry.

Position Summary

Designs, develops, and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating for defensible, valid, scalable, reproducible models (predictive or optimization) for problem solving and strategy development. Participates in internal and external communities of practice in data science/artificial intelligence/machine learning to advance knowledge in the field. Educates the non-technical community on advantages, risks, and maturity levels of data science solutions. 

This position is hybrid, working from your remote office and your assigned location based on business need. Regular presence is required in San Ramon, once every two weeks.

PG&E is providing the salary range that the company in good faith believes it might pay for this position at the time of the job posting. This compensation range is specific to the locality of the job.  The actual salary paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, and internal equity.  Although we estimate the successful candidate hired into this role will be placed towards the middle or entry point of the range, the decision will be made on a case-by-case basis related to these factors.

Bay Area Minimum: $140,000

Bay Area Mid: $189,000
Bay Area Maximum: $238,000

California Minimum: $133,000

California Mid: $180,000

California Maximum:$226,000

This job is also eligible to participate in PG&Eโ€™s discretionary incentive compensation programs. 

Job Responsibilities

  • Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
  • Creates advanced data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets
  • Extracts, transforms, and loads data from dissimilar sources from across PG&E
  • Applies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models that involve multiple facets and iterations in algorithm development. 
  • Writes and documents reusable python functions and modular python code for data science.
  • Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
  • Works with sponsor departments and company subject matter experts to understand application and potential of data science solutions that create value.
  • Presents findings and makes recommendations to senior management.
  • Act as peer reviewer of complex models 

Qualifications

Minimum:

  • Bachelorโ€™s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field
  • 6 years in data science OR no experience, if possess Doctoral Degree or higher, as described above

Desired:

  • Doctorate Degree in Data Science, Machine Learning, or job-related discipline or equivalent experience
  • Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
  • Active participation in the external data science/artificial intelligence/machine learning community of practice, as demonstrated through volunteering in professional organizations for the advancement of the field, presentations in conferences or publications to disseminate data science knowledge and topics, or similar activities.
  • Knowledge of industry trends and current issues in job-related area of responsibility as demonstrated through peer reviewed journal publications, conference presentations, open source contributions or similar activities
  • Competency with commonly used data science and/or operations research programming languages, packages, and tools for building data science/machine learning models and algorithms  
  • Proficiency in explaining in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
  • Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders
  • Mastery of the mathematical and statistical fields that underpin data science, specifically focused in reliability and failure analysis
  • Demonstrated proficiency in enterprise data platforms and analytics tools, including Foundry, SAP, and Power BI, with the ability to integrate and analyze data across ERP systems and visualization environments.