Wish is a mobile e-commerce platform that flips traditional shopping on its head. We connect hundreds of millions of people with the widest selection of delightful, surprising, and—most importantly—affordable products delivered directly to their doors. Each day on Wish, millions of customers in more than 160 countries around the world discover new products. For our over 1 million merchant partners, anyone with a good idea and a mobile phone can instantly tap into a global market.
We're fueled by creating unique products and experiences that give people access to a new type of commerce, where all are welcome. If you’ve been searching for a supportive environment to chase your curiosity and use data to investigate the questions that matter most to you, this is the place.Job Description
At Wish, our Data Science & Engineering team is composed of Data Scientists, Data Analysts & Data Engineers who focus on centralizing corporate data in order to gain insights, knowledge and scalability, that empower a proactive and rigorous analysis of key business indicators. Our mission is to derive wisdom from data via the application of Data Science.
Wish has exciting opportunities for talented Staff Data Scientists on our Buyer Risk Data Science team. This is a unique opportunity to lead development and deployment of Machine Learning models to address complex business questions such as fraud detection, account takeover detection and anomaly detection at large scale. Successful candidates will have extensive backgrounds in quantitative fields and significant experience with Machine Learning model development and deployment.
- (Required) Energetic and flexible. We own the actions. We own the impact. We iterate fast because fraudsters do. And we take fraud seriously.
- (Required) Tech lead and role model. You are the team’s role model for technical excellence and communication style. You will lead the technical decisions and bring up the team’s ML capabilities in one or more major areas (e.g. transaction security, account security, graph models, deep learning, real time streaming, data augmentation, etc.)
- (Required) Theory and practice of Machine Learning including Deep Learning. 5+ years of hands-on industrial experience on most ML/DL algorithms and big data technologies. We solve problems with advanced skills, and we take pride in our work.
- (Required) System design and programming. 5+ years of hands-on industrial experience with ML system design and implementation. We productionize code ourselves, and we love it to be clean.
- (Required) ML Engineering. Hands on experience developing and deploying large scale, high throughput, low latency, real time ML systems.
- (Required) Product sense. You always start from business problems, not technical details. Even better, you start from the press release of the final product, and the FAQ you might anticipate from customers, management and stakeholders.
- (Required) Communication. You enjoy managing stakeholders, complex multi-team project management, taking end-to-end responsibilities, and ownership over a project.
- (Preferred) Education. Ph.D. in computer science, or a related quantitative field, from a top university.
- (Preferred) Top talent and thought leader. Publications at top Machine Learning conferences; ML patents and/or significant contribution to the open source community.
- (Preferred) Domain expertise. Previous experience in fraud detection and the unique challenges applying ML in this area.
Wish values diversity and is committed to creating an inclusive work environment. We provide equal employment opportunity for all applicants and employees. We do not discriminate based on any legally-protected class or characteristic. Employment decisions are made based on qualifications, merit, and business needs. If you need assistance or accommodation due to a disability, please let your recruiter know. For job positions in San Francisco, CA, and other locations where required, we will consider for employment qualified applicants with arrest and conviction records.