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.

Wish has exciting opportunities for talented full stack Data Scientists on our Buyer Risk Data Science team. This is a unique opportunity to lead end to end research, development and deployment of Machine Learning models to address complex business questions such as fraud detection, account takeover detection, graph data 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, as well as making impact with the end to end closed loop of data -> insights -> actions -> feedback.

In short, we are looking for people strong in: Machine learning theory and practice, software engineering, and business acumen. If you are confident in all three of above, please skip the rest of the job description and click the APPLY button. Otherwise, if you are confident in two of the three, please read on.

What you'll be doing:

• You are a full stack DS. You own all aspects of the risk domain: data analytics, research, development, deployment and monitoring. You own large projects end to end, with concrete impact, through the closed loop of data -> insights -> actions -> feedback. 
• You start from the actions, identify the insights and data needed, and prioritize by the final impact. Even better, you start from the press release of the final product, and the FAQ you might anticipate from customers, management and stakeholders.
• You understand the dual goals of the risk domain: fighting fraud and growing the business. You can clarify strategic and tactical objectives and prioritize tasks for yourself and the team. 
• You proactively watch for signs of trouble, articulate with data, and craft hotfixes or long term solutions, depending on the situation and your judgement.
• You own foundation work that enables others and other teams. You are also the team’s go to person for a large area of expertise, be it account security, transaction security, anomaly detection, graph data, real-time streaming, or a complete new field you bring into the team or company.
• You enjoy managing stakeholders, complex multi-team project management, taking end-to-end responsibilities, and ownership over a project. 

• Energetic and flexible. We own the actions. We own the impact. We iterate fast because fraudsters do. And we take fraud seriously.
• 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 projects (e.g. transaction security, account security, graph models, anomaly detection, deep learning, real time streaming, data augmentation, etc.)
• Theory and practice of Machine Learning including Deep Learning. 3+ 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.
• System design and programming. 3+ years of hands-on industrial experience with ML system design and implementation. We productionize code ourselves, and we love it to be clean.

Preferred Qualifications:

• ML Engineering. Hands on experience developing and deploying large scale, high throughput, low latency, real time ML systems.
• 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.
• Communication. You enjoy managing stakeholders, complex multi-team project management, taking end-to-end responsibilities, and ownership over a project. 
• Education. Ph.D. in computer science, or a related quantitative field.
• Top talent and thought leader. Publications at top Machine Learning conferences; ML patents and/or significant contribution to the open source community.
• 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.

Individuals applying for positions at Wish, including California residents, can see our privacy policy here.