Lead Data Scientist, Strava
$230-255k
3+ days a week in office
Social network for tracking run and cycle routes
Be an early applicant
Social network for tracking run and cycle routes
501-1000 employees
Be an early applicant
$230-255k
3+ days a week in office
501-1000 employees
Company mission
To create the most committed, close, and engaged athlete community on the internet.
Role
Who you are
- Educational Background: You have an MS degree or equivalent experience in Computer Science, Mathematics, Statistics, or a related quantitative field
- Experience: You bring 5+ years of experience in data science roles, with a consistent track record of driving impactful solutions
- Machine Learning Expertise: You have hands-on experience with various ML techniques, including supervised and unsupervised learning, and are comfortable working with deep learning models such as transformers or LLMs
- Experimentation & Statistical Analysis: You have a solid grasp of A/B testing, causal inference, and statistical methodologies to support meticulous data-driven decision-making
- Cloud & Deployment: You have experience deploying ML models in production using cloud platforms like AWS (or equivalent)
- Analytical & Problem-Solving Skills: You excel at taking on complex problems, uncovering insights, and driving data-driven strategies
- Communication & Collaboration: You are skilled at explaining complex data concepts to diverse audiences and thrive in a cross-functional environment
What the job involves
- As a Lead Data Scientist, you will play a key role in shaping the future of data-driven decision-making at Strava
- You will develop and deploy cutting-edge machine learning models, design rigorous experimentation frameworks, and uncover insights that drive impactful business and product decisions
- Working alongside cross-functional teams, you will help harness Strava’s vast dataset to enhance athlete experiences and drive engagement
- Develop and enhance machine learning models, leveraging supervised, unsupervised, and reinforcement learning techniques to enhance the athlete experience on Strava continuously
- Design and implement experimentation strategies, such as A/B testing and causal inference, to drive data-informed product and business decisions
- Work closely with product managers, engineers, marketing teams, and other partners to develop data-driven solutions that improve athlete engagement and business outcomes
- Apply expertise in large-scale data analysis to identify trends, uncover opportunities, and inform strategic decision-making
- Stay ahead of the latest industry trends in machine learning, LLMs, transformers, and deep learning, evaluating their potential impact on Strava’s data capabilities
- Mentor other data scientists, contribute to knowledge sharing through blog posts or tech talks, and help uplevel the data science capabilities
- You will be successful here by:
- Demonstrating technical excellence in machine learning, data analysis, and experimentation methodologies
- Driving collaboration across teams to ensure data science solutions align with business goals
- Communicating complex data concepts effectively to both technical and non-technical stakeholders
- Continuously seeking opportunities to optimize and innovate Strava’s data science practices
- Championing a culture of learning, mentorship, and knowledge sharing within the data science team
Our take
Strava has created an online network where runners, swimmers and cyclists can record fitness activities, and compare and compete with their community. It offers both a free and premium subscription service with added features. The company also partners with local councils and urban planners who purchase valuable journey data from Strava which can be used to map out cities and develop safer cycle paths.
The platform helps members discover and plan workouts, as well as offering a leaderboard which is updated using GPS as users compete for the top spot on particular fitness segments.
With over 125 million athletes and growing, Strava released several new product rollouts in 2024, including an AI-enabled leaderboard. A partnership with the wearable fitness tracker Oura will mean Strava software is available on wearables, taking Strava into fresh competition with the likes of Peloton and Apple.
Freddie
Company Specialist at Welcome to the Jungle
Insights
-6% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Nov 2020
$110m
SERIES F
Oct 2014
$18m
LATE VC
Total funding: $151.4m
Company benefits
- Competitive base salary & stock options
- 100% company paid benefits for employees and families
- Flexible paid time off
- $2,000 annual professional development stipend
- Paid time off for volunteering
- 401(k) plan - with company matching
- $1000 annual gear stipend
- $500 annual gym or coaching reimbursement
- On-site fitness rooms with showers, lockers, and towel service
- Weekly team workouts – including remote employees
- Safe and secure bike storage on-site
- Weekly all hands meetings
- Employee resource groups
- Anti-racism nonprofit company matching program
- Free lunch on Wednesdays on-site
- Regular team happy hours
- Team offsites and company retreats
- Cell phone reimbursement
- Generous industry discounts on gear and activities
- Race entries to events we sponsor
- Snacks and stocked kitchens on-site
- Strava gear
Company HQ
Mission District, San Francisco, CA
Leadership
Mark Gainey
(Chairman)Having studied at Harvard, Mark started their career as a TA Associates Associate before co-founding Kana Communications and several Board Membership roles. They co-founded Strava in 2007, serving since as Chairman.
Michael Horvath
(CEO & Board Member)Michael co-founded Kana with Mark before working as an Economics Professor at Stanford and Dartmouth. They worked for 4 years as CFO of GlycoFi before co-founding Strava, serving initially as CEO and since 2017 as a Board Member.
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