Closed listing
Data Scientist, Decisions - Mapping
- Toronto, ON, Canada
Full-time
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Full-time
- Closing date
- Experience
- 1+ years experience in a data science role or analytics role
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
As a Data Scientist on the Mapping team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our spatial data and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers.
Data Science Is At The Heart Of Lyft’s Products And Decision-making. You Will Leverage Data And Rigorous, Analytical Thinking To Shape Our Mapping Products And Make Business Decisions That Put Our Customers First. This Will Involve Identifying And Scoping Opportunities, Shaping Priorities, Recommending Technical Solutions, Designing Experiments, And Measuring The Impact Of New Features. You Will Help Us Solve Some Of The Most Impactful Problems In Mapping, Including
- How do we improve the quality of our map data in order to improve our recommendations?
- How do we benchmark and measure the success of our services?
- How do we validate features of the real world that affect our routing algorithms?
- Are we meeting our travel estimation promises to our customers?
- Leverage data and analytic frameworks to identify opportunities for growth and efficiency
- Partner with product managers, engineers, and operators to translate analytical insights into decisions and action, and implement products to drive business goals
- Design and analyze online experiments; communicate results and act on launch decisions
- Develop analytical frameworks to monitor business and product performance
- Establish metrics that measure the health of our products, as well as rider and driver experience
- Identify and drive impact and alignment, shaping product and business strategy through data-centric presentations
- Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
- 1+ years experience in a data science role or analytics role
- Proficiency in SQL - able to write structured and efficient queries on large data sets
- End-to-end experience with data, including querying, aggregation, analysis, and visualization
- Experience in programming, especially with data science and visualization libraries in Python or R, and machine learning libraries such as PyTorch, TensorFlow, Keras
- Experience in online experimentation and statistical analysis, and communicating results and recommendations to senior stakeholders
- Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners
- Experience in applying machine learning techniques a plus (e.g. reinforcement learning) to solve customer problems (e.g. personalization, segmentation)
- Experience working with ETL pipelines a plus
- Extended health and dental coverage options, along with life insurance and disability benefits
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- Access to a Lyft funded Health Care Savings Account
- RRSP plan with company match to help save for your future
- In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
- Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
- Subsidized commuter benefits and Lyft ride credits
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule - Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the Toronto area is CAD $88,000 - CAD $110,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.
This job fills an existing vacancy.
More about this job
Responsibilities
Use data and analytical frameworks to identify opportunities, improve mapping products, and guide product and business decisions. Design and analyze experiments, establish performance and customer-experience metrics, and communicate findings to cross-functional partners.
Requirements
A quantitative degree or relevant work experience and at least one year in data science or analytics are required, along with strong SQL and end-to-end data analysis experience. Candidates should have programming experience in Python or R, familiarity with data science and machine learning libraries, and experience with experimentation, statistical analysis, and communicating recommendations to stakeholders.
Skills
- Data Science
- SQL
- Python
- R
- Data Analysis
- Data Visualization
- Machine Learning
- PyTorch
- TensorFlow
- Keras
- Online Experimentation
- Statistical Analysis
- ETL Pipelines
- Spatial Data
- Product Analytics
- Cross-Functional Collaboration
Benefits
- Extended Health Coverage
- Dental Coverage
- Life Insurance
- Disability Benefits
- Mental Health Benefits
- Family Building Benefits
- Child Care Benefits
- Pet Benefits
- Health Care Savings Account
- RRSP With Company Match
- Paid Time Off
- Paid Parental Leave
- Commuter Benefits
- Lyft Ride Credits
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Science & Research
- Technology
- Transportation
Keywords
- Data Science
- Mapping
- Spatial Data
- Route Recommendations
- Travel Time Estimation
- SQL
- Python
- R
- PyTorch
- TensorFlow
- Keras
- Machine Learning
- Reinforcement Learning
- Online Experiments
- Statistical Analysis
- Data Querying
- Data Aggregation
- Data Visualization
- ETL Pipelines
- Analytical Frameworks
- Product Performance Metrics
- Rider Experience
- Driver Experience
- Product Strategy
- Business Strategy
- Personalization
- Segmentation
- A/B Testing
- Cross-Functional Collaboration
- Navigation