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.
