Civic Data Analyst; Sustainable Mobility

Civic Data Analyst (Sustainable Mobility)

Department: Planning

Employment Type: Full Time

Location: Denver, CO

Compensation: $65,000 - $80,000 / year

Alta Planning + Design seeks a Civic Data Analyst (Sustainable Mobility) for our Denver office. This position is a great opportunity for someone who believes in the importance of active, multimodal, and sustainable transportation and who is interested in growing their career as a professional working at the intersection of civic data and sustainability.

Serve as a technical expert and analyst across various disciplines, project types, and regions. Develop prototypes of repeatable analysis in R, Python, and GIS to advance place-based sustainable transportation solutions. Over time, foster an entrepreneurial approach to analysis through staff training, research, tool development, and custom web applications.

Engage across Alta’s disciplines to understand data analytics needs, priorities, and expectations, fostering a data-informed decision-making culture. Lead the development of new analytical products that align with the firm's objectives and the multidisciplinary nature of the practice. Collaborate closely with planners, designers, and engineers in tasks related to data analysis and visualization, ensuring the developed solutions bring valuable mobility insights and can scale organization wide.

Delve into data analysis and visualization components of client projects and R&D efforts, employing complex methodologies. Address mobility and access challenges through innovative analytical solutions, and articulate data-driven narratives effectively through reports, technical memos, and presentations. Be proactive in identifying labor-intensive processes and analysis, exploring avenues to streamline and automate them to create organization-wide value. Work on a range of projects including active transportation plans, safety action plans, complete streets planning, safe routes to school, new mobility plans, and economic benefit studies.

Each day, you will keep a community-focused perspective by pushing forward solutions that help communities inform narratives about people, address multifaceted community goals, prepare communities for change, and build a more just transportation system.

Required

• Bachelor’s Degree in Statistics, Mathematics, Computer Science or another quantitative field with demonstrated experience in the transportation planning field, OR a Bachelor’s Degree in Planning, Landscape Architecture, Environmental Sciences, or Engineering with some experience in the software development and/or data science fields.
• Proficiency in Python and/or R, SQL
• Proficiency in Quantitative Analysis: A solid background in data analysis, cross tabulation, and data interpretation is essential. Candidates should be able to apply data driven techniques to inform evidence-based decision-making in planning and design contexts.
• Strong understanding of databases, GIS, coding, and familiarity with transportation planning at an advanced level.
• GIS Proficiency - both open-source (PostGIS, QGIS, geopandas, etc.) and the ESRI suite (ArcGISPro, Spatial Analyst, Network Analyst, etc.).
• Ability to create informative data visualizations through code (e.g. D3, ggplot, matplotlib, plotly, kepler.gl, etc.).
• Experience designing, implementing, and documenting analytical solutions using code. Ability to execute an analysis entirely with code.
• Data specifications & database acronyms like OSM, MDS, GTFS, GBFS, GPS, CDS don’t scare you.
• Proficient in MS Excel, Word, PowerPoint, similar products.
• Strong written and verbal communication skills.

Additional

• Master’s Degree in Urban Planning, Statistics, Data Science, Engineering, Math, or Social Sciences
• 1+ years of experience in a consulting environment or public entity. You have experience working on responses to public sector requests for proposals.
• AICP Certification.
• Experience using Deltek VantagePoint.
• Active participation in industry-relevant professional associations and committees.
• Demonstrated work of applied statistics or machine learning techniques to transportation challenges.
• Basic familiarity with deploying…