Water Conservation Data Analyst

Summary•Vail, CO

1d•$85,259 - $119,330•Hybrid

About The Position

The Water Conservation Data Analyst plays a crucial role in our mission to protect and sustain our water resources. As a key team member in the Water Conservation Department, you will use data analysis to support water conservation goals, create water-saving strategies, and help shape a sustainable future for our community. You will support programs to manage water use across our customer types and influence conservation through data-driven insights. We’re seeking an individual passionate about using data in an environmental sustainability and water conservation setting. If you thrive on data analysis, enjoy collaborating with diverse teams, and are excited about creating positive change, this role could be a perfect fit. The work you will do as a Water Conservation Data Analyst will allow you to make a real difference in creating a sustainable future for the community where we live, work and play.

Requirements

Bachelor's degree from an accredited college or university with significant course work in environmental science, conservation, biological science, hydrology, data analysis, or related fields, AND Minimum two years of professional experience in a data analysis-heavy field, OR any combination of experience and training that would provide the required knowledge and abilities.
Use critical thinking to address data discrepancies, quality-check datasets, and support solution development through comprehensive analysis.
Ability to work across all departments and manage workloads.
Project management skills
Advanced skills in querying, data extraction, transformation, aggregation, and optimization
Experience with R and R Studio/VS Code for data manipulation, statistical analysis, and modeling
Proficiency in statistical software and libraries (e.g., pandas in Python, dplyr in R) for advanced data manipulation and analysis.
Ability to incorporate Git version control into workflows for reproducible code, CI/CD DevOps, and collaboration amongst data colleagues.
Strong foundational Excel skills for supplemental analysis (Pivot Tables, Conditional Formatting, Index Match, Data Validation).

Nice To Haves

SQL Server (Data Warehousing, ETL)
Ability to use APIs to integrate data from external sources.
Power Platform Experience using Virtual Machine (VM) Environments
Python
Docker
Understanding of data governance, privacy, and security best practices, including compliance with CISA (Cybersecurity and Infrastructure Security Agency) standards.

Responsibilities

Use data to support business decisions about water conservation and other internal initiatives and track the impacts resulting from our work.
Lead sophisticated statistical analyses of water use to refine conservation needs and understand how factors such as outreach, weather, and rates affect customers' water use.
Build regression and time-series models to quantify how weather, rate changes, and outreach affect water use, and forecast future demand and revenue under different rate and conservation scenarios.
Develop and maintain reproducible data pipelines, analysis scripts, and interactive tools (R, Quarto, Shiny) using version control, and audit and QC source data for accuracy before it drives analysis, reporting, or billing.
Develop and manage interactive dashboards, charts, and reports in Power BI and Shiny to communicate key findings internally and for the public.
Partner with departments across the organization to design customer communications and support water conservation and rate initiatives.
Serve as a subject-matter resource on water-use data and analysis for other teams and leadership and help onboard and mentor interns and analysts on tools, methods, and best practices.
Translate complex analyses into clear narratives and visuals for non-technical audiences, present findings at internal meetings, town halls, and stakeholder sessions, and respond to occasional technical customer inquiries about water use, bills, and rates.
Apply best practices in water conservation and data-driven rate structures, and maintain SOPs, reports, records, and documentation so analyses and processes remain reproducible and transferable across the team.