Data Science, Decisions - Airports
The Data Scientist will use experimentation, statistical analysis, and large-scale data to improve Lyft’s airport marketplace, identify growth opportunities, and guide product decisions. The role requires 4–6+ years of data science or analytics experience, strong SQL and Python skills, and effective cross-functional communication.
About the job
Responsibilities
- Define and implement decision frameworks, measurement strategies, and scientific methodologies for business decisions and forecasts.
- Design and analyze experiments with data science, product, and engineering teams; communicate findings and support launch decisions.
- Analyze large datasets to identify patterns, root causes, growth opportunities, and efficiency improvements; recommend technical solutions.
- Understand airport marketplace dynamics and propose enhancements to airport products.
- Present findings, recommendations, and results to senior leadership and cross-functional stakeholders.
- Establish metrics measuring product, business, rider, and driver experience health.
Requirements
- Degree in a quantitative field such as Statistics, Economics, Computer Science, Engineering, or Applied Mathematics, or equivalent practical experience; advanced degrees preferred.
- 4–6+ years of industry experience in data science or analytics.
- End-to-end data experience, including querying, aggregation, analysis, and visualization.
- Experience designing and analyzing experiments, including user and time splits.
- Ability to manage, influence, negotiate, and inspire others in a fast-moving environment.
- Proficiency in SQL and Python.
- Experience owning multiple analytical projects with ambiguous problem definitions and cross-functional integration.
- Exceptional communication skills with technical and non-technical audiences.
Benefits
- Extended health and dental coverage, life insurance, disability benefits, and mental health benefits.
- Family-building, child-care, and pet benefits.
- Lyft-funded Health Care Savings Account.
- RRSP plan with company match.
- Flexible paid time off for salaried employees; hourly employees receive 15 days paid time off plus annual increases.
- 18 weeks of paid parental leave top-up.
- Subsidized commuter benefits and Lyft ride credits.
Compensation
- Expected base pay range: CAD $108,000–$135,000.
Skills
SQL, Python, Experimentation, Data Analysis, Data Visualization, Statistical Modeling, Forecasting, Metrics, A/B Testing, Data Querying
Similar jobs
Data Science jobs
Lyft
Toronto, Canada
The Data Scientist will develop and productionize algorithms for routing, travel-time estimation, and traffic detection using geospatial, behavioral, and mobility data. The role requires 3+ years of production machine learning or data science experience and strong quantitative expertise.
Sardine
Europe
Data Scientist builds and deploys ML models to combat fraud, collaborates with clients on risk solutions, and scales models to production. Requires 5+ years in data science, Python/SQL/Spark proficiency, and strong communication skills.
Lyft
Toronto, Canada
Design and deploy optimization algorithms and incentive systems that improve driver engagement, marketplace efficiency, and earnings. The role partners with product, engineering, and operations teams and requires Python, quantitative modeling, experimentation, and at least two years of relevant experience.
Coalition Security
United KingdomThe Senior Data Scientist develops statistical and machine learning models from insurance and cybersecurity datasets to improve underwriting, pricing, risk evaluation, and workflow automation. The role requires a quantitative bachelor's degree, 5+ years of insurance experience, advanced SQL, and Python or R expertise.
Mozilla
United StatesLeads the strategy, measurement, and capability development for Firefox Marketing Data Science, covering attribution, campaign performance, budget optimization, customer insights, and scalable reporting. Requires 6+ years of marketing data science experience plus talent leadership and strong stakeholder communication.