Associate Data Scientist, Hayden AI

• Master's in Data Science, Statistics, Computer Science, Economics, Transportation Engineering, or a related field
• 6+ months of Data Science related work, projects or internships
• Strong SQL skills and experience working with data warehouse systems such as Amazon Redshift, Google BigQuery, or Snowflake
• Strong knowledge of Python for data manipulation and analysis (e.g., Pandas, NumPy)
• Experience with dbt, AWS Glue, or similar data transformation and pipeline tools
• Experience building and maintaining dashboards in BI tools such as Tableau or Looker
• Solid understanding of descriptive statistics and ability to interpret analytical results
• Strong communication skills with the ability to present findings to both technical and business audiences

Desirable

• Hayden AI seeks a Data Analyst to support a diverse set of stakeholders with Data and Analytics needs
• This is a great opportunity for someone who wants to deliver a big impact: you’ll be supporting the Data Science team and operate at the intersection of Data Engineering, Analytics and Data Science
• You will work with transit agencies, the customer success team, finance, product, company executives, and engineers
• You will enable all of them to get their data questions answered in a timely manner with a high accuracy
• Create and improve standardized metrics from foundational datasets using dbt models and AWS Glue jobs
• Create and improve compelling data stories, visualizations and dashboards based on stakeholder and UX feedback
• Create data reports that answer ad hoc requests from cross-functional teams for impact analyses, anomaly investigations and root cause analyses, etc
• Serve as first responder for data discrepancy and freshness issues
• Translate business questions into data requirements, acting as the interface between customer-facing teams and the data team
• Monitor data quality and completeness in data processing steps across multiple fleets, flagging issues and driving fixes
• Support data scientists by preparing datasets, performing exploratory analysis, and providing review and feedback on team analyses
• Communicate findings and recommendations clearly to both technical and non-technical stakeholders