The Position

Only the first 100 qualified applications will be accepted by the Recruitment Division online at www.ebmud.com during the filing period.

NOTE: Concurrent to this recruitment, we are also recruiting for Data Scientist II. Applicants who may be interested in both positions must submit separate applications for both recruitments.

At East Bay Municipal Utility District (EBMUD), data science and analytics play an increasingly vital role in protecting public health, ensuring environmental sustainability, and delivering safe, reliable, affordable water and wastewater services to 1.4 million customers in the East Bay. From predicting pipeline failures to analyzing water quality and supporting climate resilience strategies, the work of the Data Scientist position will directly support critical infrastructure, the communities we serve, and the environment we protect.

The position supports Departments and teams across the organization by applying data science techniques to solve complex problems, improve operations, and inform decision-making. This role involves working with diverse datasets and tools to analyze trends, develop models, and deliver actionable insights that guide EBMUD policies, services, and programs.

Data Scientist I is the entry-level role, ideal for emerging data science professionals ready to apply analytical methods to real-world challenges. Under guidance, incumbents support cross-departmental projects through data collection, analysis, and visualization that inform operational and strategic decisions. This role is flexibly staffed with the Data Scientist II classification, and advancement may be possible with demonstrated proficiency and time completed in Data Scientist I position.

The duties of the Data Scientist positions include the following:

Collects, cleans, and preprocesses structured and unstructured data from a variety of internal and external sources.
Designs, develops, and applies statistical models, machine learning algorithms, and artificial intelligence techniques to derive insights and support decision-making.
Builds and evaluates predictive and classification models using techniques such as regression, clustering, natural language processing (e.g., entity extraction from inspection logs), and time series forecasting (e.g., predicting pipeline failures or demand trends).
Translates complex analytical results into clear, actionable recommendations for Department and operational stakeholders.
Collaborates with cross-functional teams to define data problems, develop project scopes, and deliver end-to-end analytical solutions.
Creates dashboards, interactive visualizations, and reports using matplotlib, seaborn, Plotly, and BI platforms (e.g., Tableau, Power BI) to support decision-making by analysts, engineers, managers, and executive leadership.
Maintains data integrity, governance, and security while working with sensitive or confidential datasets.
Develops documentation and may train others in the use of analytical tools, models, and related methods.
Utilizes automated or computer-based work management systems in the course of work.
Performs other related duties and responsibilities as required.

The ideal candidate is a data science professional who is passionate about applying advanced analytics, machine learning, and AI to solve real-world problems in the public sector. This candidate combines technical expertise with strong communication skills and a collaborative mindset. They will be comfortable working with diverse datasets, deriving insights from complex information, and translating technical results into actionable recommendations for non-technical stakeholders.

The ideal candidate will have foundational knowledge of or exposure to:

Statistical analysis, data mining techniques, and machine learning algorithms
Basic understanding of how data science and machine learning can help solve operational or business challenges
Data visualization tools and techniques to communicate findings effectively
The Python data science ecosystem, including libraries such as NumPy, pandas, scikit-learn, matplotlib, and seaborn
Other programming and data analysis tools such as R and SQL
Database design, management systems, and principles of data integrity and security

They Will Also Demonstrate The Ability To

Collect, clean, and preprocess data from a wide range of sources
Detect, diagnose, and correct issues with data quality or integrity
Develop and validate models using statistical, machine learning, and AI techniques
Apply both supervised and unsupervised learning to support predictive and prescriptive analytics
Interpret complex datasets and translate insights into practical, actionable recommendations
Communicate technical concepts clearly to non-technical audiences through visualizations, presentations, and written reports
Show willingness to learn and grow in data science skills and tools
Work collaboratively with cross-functional teams and maintain effective relationships across the organization
Work effectively on projects with guidance, while contributing to team goals and deadlines
Manage multiple priorities, meet deadlines, and coordinate efforts across departments

The salary range is $10,279 per month, increasing to $10,793, $11,333, $11,900, and $12,495 after 6, 18 and 30 and 42 months respectively.

EBMUD is an Equal Opportunity Employer. All qualified candidates will receive consideration for employment without regard to race, color, religion, creed, sex, gender, gender identity (including transgender status), gender expression, marital or registered domestic partnership status, age for individuals age forty or older, national origin, ancestry, disability (mental or physical), medical condition (cancer and genetic characteristics), genetic information, sexual orientation, military and veterans status, family or medical leave status, pregnancy (including childbirth, lactation or related medical condition), pregnancy disability leave status, domestic violence victim status, political affiliation, and other categories protected by federal, state and/or local laws.

Requirements

A bachelor’s degree or its equivalent* with major coursework in data science, statistics, computer science, engineering, or a related field
Six months of experience in data analysis, statistical modeling, or a related field. This experience requirement can be met through equivalent paid internships or traditional employment.
Four years or more of full-time equivalent experience in data analysis, statistical modeling, or a related field may substitute for the education requirement.

Equivalent combinations of education and experience may be considered. To be considered under the “equivalent combination of education and experience” provision, it is your responsibility to include in your application materials written evidence of employment performed at the level of the typical duties of this position and/or coursework in subject areas directly related to this position. For more information, see our FAQ page at http://www.ebmud.com/jobs/job-resources/job-faqs-frequently-asked-questions/.

The Selection Process

Submit a completed EBMUD application and the required supplemental question responses online at www.ebmud.com by 4:30 p.m., Friday, August 8th, 2025. Only application materials submitted online during the filing period will be accepted.
Candidates must achieve a passing score on each test part in order to advance to the next step in the selection process.
Qualified applications within the limit and supplemental responses will be competitively evaluated, with those candidates receiving a passing score to be invited to a panel interview tentatively scheduled for September.
Successful candidates will be placed on the hiring list, based on rank, for further consideration to fill the current regular vacancy, as well as others occurring over the next 12 to 24 months.
The probation period for this position is 12 months. For those holding civil service status the probation period is 6 months.
All employment offers are conditional, pending the results of a Live Scan background screening. All selected finalists must participate in the Live Scan background screening process to remain in consideration for EBMUD employment.

Supplemental Information

As the first step in the selection process, responses to the supplemental questions must be submitted online with the regular EBMUD application. Please provide concise and clear responses to each question below. Your responses should accurately represent the roles, responsibilities and education described in your application. Please limit your response to 350 words or less for each question. Should you respond with comments such as “see application” or “see resume” instead of addressing the questions directly, your application may not be considered.

Our Excellent Benefits Package Includes

Eligibility for annual merit-based bonus pay program;
12 days paid vacation; 16 holidays; 13 days paid sick leave;
Family health insurance (choice of Kaiser fully paid or Sutter Health Plus or Anthem Blue Cross 85% paid);
Fully paid family dental and vision care plans; life insurance; long-term disability insurance;
EBMUD Retirement Plan (reciprocal with CalPERS);
$1,000/yr. contributed to flexible spending account or cash;
$145/mo. public transit subsidy;
401(k), 401(a) and 457(b) tax-deferred retirement plans; Roth 401(k);
$3,500/yr. tuition reimbursement;
And opportunities for professional growth including training and career development.

01

Applicants must reside within commuting distance of EBMUD’s Oakland, CA Administration building. EBMUD will not provide relocation assistance. A hybrid telecommuting schedule may be possible after an initial period entirely in the office, but this is not guaranteed, would require a minimum of two to three days in the office, and is subject to change.

I accept these in-office requirements.
I do-not accept these in-office requirements.

02

Concurrent to this recruitment, we are also recruiting for Data Scientist II. Applicants who may be interested in both positions must submit separate applications for both recruitments.

I acknowledge

03

What experience do you have using Python or other tools to explore and analyze data? Share a specific example that highlights the techniques or libraries you used, how you worked with the data, and how you shared or explained your findings—especially to people who weren’t technical. You may also include any data visualization tools (like Excel, Tableau, or Python libraries) that helped you communicate your analysis.

04

Please describe any experience you have working with data systems or data pipelines. This could include working with structured or unstructured data, helping move or transform data (ETL/ELT), or supporting data analysis in cloud or on-premises environments. Include any tools or platforms you've used and describe how you contributed to ensuring data was accurate, organized, or ready for analysis.

05

How does your background and experience in data science prepare you to support the work of a water and wastewater utility like the East Bay Municipal Utility District?

Required Question

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