Product Data Scientist

Product Data Scientist

The Data team leverages data from our autonomous vehicles, operations, and rider experience to enhance driving performance and service readiness. We provide the foundation for strategic decision-making, enabling our stakeholders to make trusted decisions faster and gain deeper insight into their problems.

The Data Scientist in this role will serve our Product and Operations stakeholders as we prepare for commercial launch. This role will be key to prioritize product features, investigate hypotheses, uncover insights, and guide the Product team to data-driven decisions. You will bring not just analysis and experimentation skills, but also the curiosity to discover and dig deeper into data as well as the ownership to propose novel solutions to problems in this space. As a result, your work will accelerate our understanding of our service so we can provide a convenient, safe, and delightful experience for our riders.

Responsibilities

• Coordinate with Product, Operations, and Engineering stakeholders to understand product requirements and problem statements
• Process, clean, and validate the data to be used in analysis
• Partner with data engineers to enhance data collection and transformation methods when needed
• Analyze data to describe and diagnose our service performance and implement analytical models into production
• Propose, test, and validate hypotheses about our service and rider experience in collaboration with Product
• Present insights, findings, and solutions to stakeholders

Requirements

Qualifications

• BS/MS: 4+ years of data science and analytics experience or PhD in related discipline
• Strong fluency with Python
• Strong fluency with SQL
• Strong experience with statistical methods and mathematical models
• Strong written and verbal communication skills
• Good experience with data visualization tools (e.g. Tableau, Looker, PowerBI)
• Good experience with experimentation methods (e.g. A/B testing)

Bonus Qualifications

• Experience with predictive modeling frameworks and machine learning methods
• Experience with a workflow manager such as Airflow
• Experience with data warehouse platforms (e.g. Redshift, BigQuery, Databricks, …)
• Experience with large scale processing frameworks (e.g. Spark, Hadoop, …)
• Experience with large scale streaming platforms (e.g. Kafka, Kinesis)

Benefits

• Health Care Plan (Medical, Dental & Vision)
• Life Insurance (Basic, Voluntary & AD&D)
• Paid Time Off (Vacation, Sick & Public Holidays)
• Training & Development
• Retirement Plan (401k, IRA)