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Entry Level Climate Data Scientist Jobs in California

You will bridge science and storytelling, creating ideas that resonate globally and spark ... Translate complex ocean and climate data into engaging narratives for digital and live platforms ...

Energy Transitions Scientist

Oakland, CA · On-site +1

$89K - $102K/yr

Clean Energy Transition, Environmental Public Health, Climate, Energy Equity, and Oil and Gas. We ... Conduct data analysis, synthesize research, create and edit reports, visualize data, and lead ...

Energy Transitions Scientist

Oakland, CA · On-site +1

$89K - $102K/yr

Clean Energy Transition, Environmental Public Health, Climate, Energy Equity, and Oil and Gas. We ... Conduct data analysis, synthesize research, create and edit reports, visualize data, and lead ...

Consultant, Climate Risk

Novato, CA · On-site

$69 - $100/hr

Conducting research, client interviews, and data analytics to assess opportunities to achieve ... which entry level candidates considered based on strength of internship and other applied ...

Showing results 21-40

Entry Level Climate Data Scientist information

What does an entry level climate data scientist do?

An Entry Level Climate Data Scientist collects, processes, and analyzes environmental and climate data to help solve problems related to climate change. They use statistical and computational tools to interpret large datasets, create models, and generate insights for researchers, policymakers, and organizations. Their work supports efforts to understand weather patterns, predict climate trends, and develop strategies for sustainability. Often, they collaborate with teams and use programming languages like Python or R to organize and visualize data.

What are some typical projects or tasks that an entry level climate data scientist might work on during their first year?

As an entry level climate data scientist, you can expect to work on projects such as cleaning and organizing large climate datasets, running basic statistical analyses to identify trends, and helping to visualize data for reports or presentations. You might also assist in developing or refining climate models under the supervision of senior scientists, and collaborate with team members from environmental science, engineering, or policy backgrounds. Regularly, you’ll participate in team meetings to discuss project progress and share results, gaining exposure to interdisciplinary research and real-world climate solutions.

What are the key skills and qualifications needed to thrive as an entry level climate data scientist, and why are they important?

To thrive as an Entry Level Climate Data Scientist, you need a solid background in environmental science, statistics, and programming (typically with a degree in a related field). Familiarity with data analysis tools like Python, R, GIS software, and experience with climate data sets or machine learning libraries are commonly required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex data and present findings clearly. These skills enable accurate climate modeling and actionable insights that support impactful environmental decision-making.

What is the difference between Entry Level Climate Data Scientist vs Entry Level Environmental Data Analyst?

AspectEntry Level Climate Data ScientistEntry Level Environmental Data Analyst
Required CredentialsBachelor's in Environmental Science, Data Science, or related field; some roles prefer certifications in data analysis or climate modelingBachelor's in Environmental Science, Data Analysis, or related field; certifications in data analysis are common
Work EnvironmentResearch institutions, government agencies, climate-focused organizationsEnvironmental consulting firms, government agencies, NGOs
Employer & Industry UsageUsed in climate modeling, policy analysis, and research projectsApplied in environmental impact assessments, data reporting, and compliance

Both roles involve analyzing environmental data, but Climate Data Scientists focus more on climate models and predictive analytics, while Environmental Data Analysts handle broader environmental datasets and reporting. The roles often overlap in skills and work environments, making them common comparison points for entry-level professionals in the environmental sector.

What are the most commonly searched types of Climate Data Scientist jobs in California?

The most popular types of Climate Data Scientist jobs in California are:

What are popular job titles related to Entry Level Climate Data Scientist jobs in California?

For Entry Level Climate Data Scientist jobs in California, the most frequently searched job titles are:

What job categories do people searching Entry Level Climate Data Scientist jobs in California look for?

The top searched job categories for Entry Level Climate Data Scientist jobs in California are:

What cities in California are hiring for Entry Level Climate Data Scientist jobs?

Cities in California with the most Entry Level Climate Data Scientist job openings:

Infographic showing various Entry Level Climate Data Scientist job openings in California as of July 2026, with employment types broken down into 81% Full Time, 16% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

DATA SCIENTIST I-FINANCIAL & TIME SERIES FORECASTING

VSolvit

Norco, CA • On-site

$34.62 - $45.67/hr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 25 days ago


Job description

Job Summary

We are seeking a talented and driven Data Scientist to join our evolving and dynamic team. This position is open to candidates at entry level of experience who possess a strong mathematical foundation and a passion for predictive modeling. In this role, you will build, validate, and maintain multi-variable time series forecasting models to project financial data and agency expenditures over multi-year horizons. You will work directly with financial records, taking ownership of the data lifecycle, from scraping, joining, and transforming raw datasets to rigorous model validation. We are looking for a resourceful problem-solver who excels at mathematical modeling, adapts quickly to changing data environments, and ensures our predictive tools remain accurate and resilient.

As with any position, additional expectations exist. Some of these are, but are not limited to, adhering to normal working hours, meeting deadlines, following company policies as outlined by the Employee Handbook, communicating regularly with assigned supervisor(s), and staying focused on the assigned tasks including company meetings, and completing other tasks as assigned.

Responsibilities

  • Time Series & Mathematical Modeling: Support the development and evaluation of statistical and time series forecasting models, including ARIMA, Prophet, regression, and tree-based models.
  • Data Pipeline Construction & Scripting: Write and maintain Python scripts to scrape, extract, clean, join, and transform structured and unstructured financial data from web sources, APIs, databases, and raw files.
  • Model Validation & Quality Assurance: Execute established validation workflows, compare model performance using metrics such as RMSE, MAE, and MAPE, and identify potential data-quality or data-leakage issues.
  • Quantitative Feature Engineering: Assist with analyzing historical pricing, inflation indices, budget cycles, and spending patterns to create features for forecasting models.
  • Data Analysis & Documentation: Perform exploratory data analysis and document data sources, assumptions, transformations, model results, and known limitations.
  • Stakeholder Communication: Create reports, visualizations, and summaries that explain analytical findings to technical and non-technical stakeholders.
  • Resourcefulness & Learning: Learn new domain requirements, proprietary databases, customer tools, and forecasting methods with guidance from senior team members.
  • Compliance & Security: Maintain strict compliance with defense security protocols, confidentiality guidelines, and internal data handling policies.

Basic Qualifications

US Citizenship Required

Ability to obtain and maintain a Secret Security Clearance

  • Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Science, Economics, Finance, Engineering, or a related quantitative field.
  • Recent graduates and candidates with up to two years of relevant professional, internship, research, or academic experience are encouraged to apply.
  • Foundational knowledge of linear algebra, calculus, probability, and statistics.
  • Working knowledge of Python for data manipulation and analysis, including pandas and NumPy.
  • Academic, internship, research, or project experience involving statistical modeling, machine learning, predictive analytics, or time series forecasting.
  • Basic understanding of single-variable and multi-variable forecasting methods.
  • Understanding of model evaluation concepts, including training and test datasets, error metrics, overfitting, and data leakage.
  • Strong attention to detail and the ability to organize, document, and communicate analytical work.
  • Strong verbal and written communication skills with the ability to explain technical concepts clearly.
  • If applicable: If you are or have been recently employed by the U.S. government, a post-employment ethics letter will be required if employment is offered.

Preferred Skills and Qualifications

  • Coursework, internship, research, or project experience in Economics, Finance, Econometrics, Accounting, or time series analysis.
  • Experience with scikit-learn, statsmodels, Prophet, matplotlib, or similar analytical libraries.
  • Familiarity with SQL, APIs, web scraping, ETL processes, or data-processing tools.
  • Experience completing a capstone, thesis, internship, or personal project involving forecasting or predictive modeling.
  • Exposure to government, defense, budgeting, or financial datasets.
  • Familiarity with inflation adjustments, budget cycles, fiscal years, and macroeconomic factors.
  • Familiarity with version control tools such as Git or GitHub.
  • Continued education and interest in current and emerging AI/ML technologies.
  • Strong problem-solving skills and the ability to work in a fast-paced environment.

Company Summary

Join the VSolvit Team! Founded in 2006, VSolvit (pronounced 'We Solve It') is a technology services provider that specializes in cybersecurity, cloud computing, geographic information systems (GIS), business intelligence (BI) systems, data warehousing, engineering services, and custom database and application development. VSolvit is an award winning WOSB, CA CDB, MBE, WBE, and CMMI Level 3 certified company. We offer a customizable health benefits program that best meets the needs of its employees. Offering may include: medical, dental, and vision insurance, life insurance, long and short-term disability and other insurance products, Health Savings Account, Flexible Spending Account, 401K Retirement Plan options, Tuition Reimbursement, and assorted voluntary benefits. Our goal is to grow together and enjoy the work that we do as a team.


VSolvit LLC is an Equal Opportunity/Affirmative Action employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, national origin, protected veteran status, or disability status