We are looking for a Data Scientist to drive data-driven decision-making and evaluate the real-world impact of deployed systems. As a key member of our small but impactful team, you will work at the intersection of data analytics, machine learning, and business strategy to provide actionable insights. This role offers a unique opportunity to collaborate with transit agencies, product teams, finance, engineering, and company leadership to solve complex problems and unlock new opportunities using data.

Responsibilities

Design and implement data pipelines and ETL processes to enable efficient and reliable data access for analytics and decision-making.
Develop and maintain dashboards and reports to track key performance indicators (KPIs) and provide actionable insights to stakeholders.
Set up monitoring and alerting systems to detect anomalies and ensure data quality and system reliability.
Conduct deep-dive analyses to support day-to-day decision-making across teams, leveraging both structured and unstructured data.
Collaborate with engineering teams to ensure seamless integration of data pipelines and analytics tools into operational workflows.
Perform exploratory data analysis (EDA) to uncover trends, anomalies, and insights that inform business strategies and operational decisions.
Act as a data advocate by clearly communicating findings and recommendations to both technical and non-technical stakeholders.

Contribute to the development of scalable data science workflows and best practices within the organization.

Must have

Master's or PhD in Data Science, Statistics, Computer Science, Transportation Engineering, Economics, or a related field.
3+ years of experience in data science, machine learning, or a related field, with a track record of delivering impactful data solutions.
Proficiency in Python and experience with data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
Strong experience with SQL and working knowledge of data warehouse systems such as Amazon Redshift, Google BigQuery, or Snowflake.
Expertise in statistical analysis, machine learning algorithms, and model evaluation techniques.
Familiarity with data pipeline tools and frameworks such as Airflow, DBT, or similar.
Experience working with visualization tools like Tableau or Looker to translate insights into actionable recommendations.
Excellent problem-solving skills with the ability to analyze complex data and provide clear, data-driven insights.
Strong communication skills with the ability to present findings to both technical and business audiences.
Nice to have
Experience working with cloud platforms, especially AWS, and deploying models using cloud-based services.
Familiarity with geospatial analytics and processing spatial datasets.
Experience working with large-scale time-series and mobility datasets (e.g., GTFS, GPS traces, transit logs).
Prior experience in a startup environment and a desire to make a significant impact.