Senior Data Scientist

Responsibilities

• Design and implement data-driven solutions to support strategic decision-making across the company.
• Develop rigorous methods to assess transit performance and broader impacts across all deployment stages, controlling for confounders and external factors.
• Analyze structured and unstructured data to identify trends, anomalies, and opportunities that can enhance product offerings and operational efficiencies.
• Collaborate with engineering teams to operationalize models and ensure seamless integration into our data pipelines.
• Build and maintain dashboards and reports that track key performance indicators (KPIs) to provide transparency and drive business goals.
• Conduct exploratory data analysis (EDA) to inform product development and business strategies.
• Act as a data advocate by effectively communicating findings and recommendations to technical and non-technical stakeholders.
• Contribute to developing scalable data science workflows and best practices within the organization.

Qualifications

• Master’s or PhD in Data Science, Statistics, Computer Science, Economics, or a related field.
• 5+ 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.
• Bonus: 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.