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Senior Data Scientist, Machine Learning, Rider Recommendations

At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Data Science is at the heart of Lyft’s products and decision-making. As a member of the Rider team, you will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithms that power our internal and external products. We’re looking for passionate, driven Data Scientists to take on some of the most interesting and impactful problems in ridesharing.

As a Data Scientist specializing in Algorithms, you will develop mathematical models for the platform's core services, addressing diverse problems in optimization, prediction, machine learning, and inference. On the Rider Recommendations team, you will collaborate with cross-functional teammates and stakeholders to develop advanced machine learning models to enhance rider experience. By analyzing user behavior and leveraging data-driven insights, the team builds personalized recommendation systems that help deliver more relevant, engaging content and products. The Rider Recommendations team aims to optimize recommendations, drive user satisfaction, and improve overall platform engagement.

You will report to a Data Science Manager in the Rider Science team.

Responsibilities:

  • Drive the Science roadmap of the team’s problem area, leverage data and analytic frameworks to direct creations and improvements of algorithms and models underpinning the team’s systems and products
  • Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
  • Perform exploratory data analysis to gain a deeper understanding of the problem
  • Construct and fit statistical, machine learning, or optimization models
  • Write modeling code; collaborate with Software Engineers to implement algorithms in production
  • Design and implement both simulated and live traffic experiments
  • Analyze experimental and observational data; communicate findings; facilitate decisions
  • Develop measurement methodologies to monitor the health of our products, as well as the impacts on user outcomes and marketplace outcomes
  • Drive collaboration and coordination with cross-functional teams
  • Advise teams on best practices. Be a thought leader and go-to expert for stakeholders and dependency teams

Experience:

  • M.S. or Ph.D. in Machine Learning, Statistics, Computer Science, Mathematics, or other quantitative fields
  • 4+ years professional experience in a technology company setting
  • Proven experience with building and evaluating machine learning models
  • Proven experience in leading high visibility projects and influencing others in a cross-functional team environment
  • Proficiency with SQL, Python and working in a production coding environment
  • Passion for driving business impact with data 
  • End-to-end experience with data, including querying, aggregation, analysis, modeling and visualization
  • Strong oral and written communication skills, and ability to collaborate with and influence cross-functional and cross-team partners
  • Strong business sense and understanding of experimentation methodologies
  • Experience in online experimentation and statistical analysis.

Benefits:

  • Great medical, dental, and vision insurance options
  • Mental health benefits
  • Family building benefits
  • In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
  • 401(k) plan to help save for your future
  • 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
  • Pre-tax commuter benefits
  • Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day. 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 San Francisco area is $144,000 - $180,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

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Average salary estimate

$162000 / YEARLY (est.)
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$144000K
$180000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Scientist, Machine Learning, Rider Recommendations, Lyft

At Lyft, we're on a mission to bring people together, and as a Senior Data Scientist specializing in Machine Learning and Rider Recommendations, you'll be at the forefront of that initiative in our San Francisco office. We believe in fostering a dynamic and inclusive environment where data science is integral to our products and decision-making processes. Imagine working on fascinating problems that not only shape our core services but also enhance riders' experiences through personalized recommendations. In this role, you’ll team up with engineers, product managers, and business partners, diving into exploratory data analysis to construct and optimize mathematical models that solve real-world problems. As part of the Rider Recommendations team, you'll analyze user behavior, build advanced machine learning models, and ultimately develop data-driven insights that drive engagement and user satisfaction. Your contributions will extend to designing experiments, analyzing both experimental and observational data, and developing methodologies to monitor product health. We value passionate and driven individuals who thrive in cross-functional settings, guiding decisions with your expertise. Whether it’s construction of algorithms or advising teams on best practices, your skills in SQL and Python will empower you to influence high-visibility projects. This isn't just a job; it's an opportunity to make a tangible impact in the ridesharing industry, while enjoying benefits like unlimited PTO and comprehensive insurance options. Join us and become a vital part of our team to optimize recommendations and enrich the experience for millions of users.

Frequently Asked Questions (FAQs) for Senior Data Scientist, Machine Learning, Rider Recommendations Role at Lyft
What does a Senior Data Scientist in Machine Learning at Lyft do?

A Senior Data Scientist specializing in Machine Learning at Lyft is responsible for developing advanced algorithms that enhance the rider experience. This role involves analyzing user behavior, building mathematical models, designing and implementing experiments, and collaborating with cross-functional teams to deliver impactful recommendations.

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What qualifications are needed for the Senior Data Scientist position at Lyft?

To be considered for the Senior Data Scientist position at Lyft, candidates should possess a M.S. or Ph.D. in Machine Learning, Statistics, Computer Science, Mathematics, or related fields along with at least 4 years of experience in a technology company. Proficiency in SQL, Python, and experience in building and evaluating machine learning models are vital.

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What kind of projects would a Senior Data Scientist at Lyft be involved in?

As a Senior Data Scientist at Lyft, you'll drive the science roadmap for projects that enhance rider recommendations. This includes constructing and fitting statistical models, performing exploratory data analysis, and designing both simulated and live traffic experiments to optimize algorithm performance.

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Can you describe the team dynamics for a Senior Data Scientist at Lyft?

The team dynamics for a Senior Data Scientist at Lyft are characterized by collaboration with Engineers, Product Managers, and Business Partners. You'll work in a cross-functional environment where sharing ideas and advice is encouraged, helping shape significant business decisions and influencing product strategy.

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What roles or teams does a Senior Data Scientist at Lyft collaborate with?

A Senior Data Scientist at Lyft collaborates extensively with Engineering teams and Product Managers to frame problems mathematically and in business contexts. You'll also connect with Business Partners and other cross-functional teams, enhancing teamwork and driving the execution of data science initiatives.

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What skills are essential for a Senior Data Scientist focusing on Rider Recommendations at Lyft?

Essential skills for a Senior Data Scientist focusing on Rider Recommendations at Lyft include proficiency in SQL and Python, strong analytical capabilities, familiarity with machine learning frameworks, and excellent oral and written communication skills to effectively influence cross-functional partners.

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What are the growth opportunities for a Senior Data Scientist at Lyft?

At Lyft, a Senior Data Scientist has numerous growth opportunities including leading high-visibility projects, mentoring junior team members, and the potential to expand into leadership roles within data science or cross-departmental initiatives. Continuing education and professional development are also part of our culture.

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Common Interview Questions for Senior Data Scientist, Machine Learning, Rider Recommendations
Can you explain your experience with building machine learning models?

When discussing your experience with building machine learning models, emphasize specific projects where you applied techniques, the challenges you faced, and the outcomes. Highlight your proficiency in relevant tools and languages, such as Python and libraries like TensorFlow or Scikit-learn.

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How do you approach exploratory data analysis?

In your response, outline your step-by-step approach to exploratory data analysis, including how you define the problem, the data sources you use, and the kinds of visualizations or summaries you create to discover patterns or trends. Discuss specific tools or methods you rely on, such as pandas for data manipulation or seaborn for visualization.

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Describe a time you influenced a project decision with data.

Share a specific story where your data analysis played a crucial role in influencing a project decision. Outline the context, the analysis you performed, and how you effectively communicated the findings to stakeholders, showing the impact it had on the project direction.

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What methods do you use for performance monitoring of algorithms?

Discuss various measurement methodologies such as A/B testing and statistical control methods to monitor algorithm performance. Include how you establish baseline metrics, conduct experiments, and iteratively improve models based on data outcomes.

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How do you ensure your data analysis aligns with business goals?

Explain how you engage with stakeholders to understand their objectives and then align your data analysis methodologies to directly support those goals. This could involve discussing specific metrics that are meaningful to the business and how you ensure your recommendations are data-driven and actionable.

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Can you give an example of a challenging data problem you solved?

Share a challenging data problem you encountered, detailing the steps you took to analyze it. Describe your thought process, the tools and techniques you used, and the ultimate solution you developed, focusing on the impact it had on the organization or project.

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How do you handle conflicting priorities within cross-functional teams?

Discuss strategies for managing conflicting priorities, such as regular communication, prioritizing based on business impact, and being proactive in seeking common ground. Highlight your interpersonal skills in facilitating discussions and making data-driven recommendations in disagreements.

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What role does experimentation play in your work?

Elaborate on the significance of experimentation in your approach as a data scientist. Discuss your experience in designing and analyzing experiments, and how the results inform decision-making and model improvements, stressing the importance of a controlled environment.

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How do you keep up to date with the latest developments in data science?

Mention your commitment to continuous learning, such as attending conferences, following industry-leading blogs, taking courses, or participating in relevant online communities. Share how this ongoing education influences your work at Lyft.

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Why do you want to work as a Senior Data Scientist at Lyft?

In your answer, connect your passion for data science with Lyft’s mission. Speak to how your skills and values align with the company culture and your eagerness to contribute to innovative projects like the Rider Recommendations, enhancing user experiences through data-driven insights.

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Lyft is one of the leading ride-sharing companies in America offering services in ride-hailing, vehicles for hire, motorized scooters, a bicycle-sharing system, rental cars, and food delivery in the United States and select cities in Canada.

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BADGES
Badge ChangemakerBadge Diversity ChampionBadge Flexible CultureBadge Work&Life Balance
CULTURE VALUES
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Customer-Centric
Social Impact Driven
Rapid Growth
BENEFITS & PERKS
Maternity Leave
Paternity Leave
Flex-Friendly
Medical Insurance
Dental Insurance
Vision Insurance
Mental Health Resources
Life insurance
Disability Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
401K Matching
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
November 24, 2024

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