Staff Data Scientist - Payment
DiDi Labs, Mountain View
DiDi Labs is working to solve the world’s most challenging problems.
The International Business Technology Team is responsible for expanding DiDi’s global footprint and establishing DiDi’s global presence. This effort will leverage existing application and service infrastructure to build DiDi’s overseas products. Our team will be the vanguard of DiDi’s international expansion initiative. Here you will work to elevate the experiences of our global customers, improve DiDi’s operational efficiency and build the products that will continue to change the global transportation landscape.
- Proactively identifying and sizing business opportunities and growth enablers.
- Defining and validating novel metrics to evaluate business performance.
- Build data modeling frameworks for addressing the growth opportunity and lifting the retention rate and experience of the customers across the ecosystem.
- Establish and apply principles of the defined data strategy to routine business problems and to evaluate product features and their effectiveness.
- Develops newer techniques (for example, advanced machine learning algorithms, auto ML) by leveraging the latest trends in machine learning, artificial intelligence to train algorithms to apply models to new data sets.
- Deep dive into cases through data and ad hoc analyses, recover the ground truth of the customer behavior, preference and pain points to boost the customer engagement.
- Organize clear, understandable visualizations, dashboard and reports to communicate results to business partners, stakeholders and executive team on a regular basis, provide the insightful story from the data perspective to business owners.
- Master degree (Ph.D. is a plus) in Statistics, Mathematics, Computer Science, Engineering or a similar quantitative field, or equivalent practical experience.
- 5+ years working experience, at least 3 years in payment industry or equivalent domain knowledge.
- Strong statistics modeling, machine learning modeling skillset, hands on mastery of data manipulation and experience with data analytics tools (SQL, R, Python, Hive, Spark, etc.) and data visualization tools (Tableau, Splunk, etc.)
- Business driven thinking with insightful data interpretation, experience working in growth team is desired but not mandatory
- Creative problem solving and independent thinking skills
- Strong verbal and written communication skill in English
- Ability to collaborate well on a geo-distributed and diversity team
About the company:
DiDi Chuxing (“DiDi”) is the world’s leading mobile transportation platform. The company offers a full range of app-based transportation options for 550 million users, including Taxi, Express, Premier, Luxe, Bus, Minibus, Designated Driving, Enterprise Solutions, Bike Sharing, E-bike Sharing, Car Sharing, and food delivery. Daily rides have reached 30 million, allowing more than 31 million drivers on the DiDi platform to find flexible work and economic opportunities.
In 2017 we opened DiDi Labs, our first overseas research center, in Mountain View, California to not only be on the forefront of the most cutting-edge research and development in AI-based security and intelligent driving technologies, but also serve as the headquarters of DiDi’s international expansion. DiDi Labs offers the visibility and flexibility of a startup, with the stability of a mature company. We welcome people from all backgrounds who have the skills, passion and drive to join us in transforming the global transportation industry.
About DiDi Labs
DiDi is a ride-sharing platform dedicated to revolutionizing the way people live and move. Didi Chuxing offers a full range of on-demand mobility options, including Taxi hailing, private car hailing, Hitch (social ride-sharing), Chauffeur (designated driver), Bus, Minibus, Car Rental, and Enterprise Solutions. Our company is committed to working with communities and partners to solve the world’s transportation and environmental challenges using big data-driven deep-learning algorithms that optimize resource allocation.
Want to learn more about DiDi Labs? Visit DiDi Labs's website.
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