Sr Data Scientist Quantitative Research at Wish

Company Description
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
The Buyer Risk team at Wish has an opportunity for experienced Data Scientists in Quantitative Research in San Francisco. The role entails driving analytics insights and enabling senior leadership to make effective, analytically driven decisions, in particular areas of fraud  risk and financial efficiency. The ideal candidate should be passionate about Wish and e-commerce, has a strong analytical and consultative mindset, deep understanding of databases and data visualization, the ability to thrive in a dynamic, fast-paced environment delivering against tight deadlines, and a passion for scaling operations through automation.What you'll be doing:
Conduct insightful analysis using internal and external data (e.g. revenue, customer, merchant) to gain insights that will drive tactical and strategical business decisions.Proactively watch for signs of trouble, articulate with data, and make hot fixes before long term solutions can be deliveredConceptualize and build centralized tools (including pipelines) that can extract data/insights for daily business management in an automated manner.Develop dashboards and visualizations for the business stakeholders and maintain the integrity of the reports. Streamline and automate dashboards / reporting / pipelinesProcess a large amount of data and do deep dives to understand certain trends/patterns, carry out correlation analysis to identify causes and relatedness.Conduct deep dive for root cause analysis and causal inferenceOwn foundation work that enables others and other teamsOwn the end to end data -> insights -> actions -> feedback closed loopWork effectively with cross-functional teams globally, assimilating requirements, driving results in the form of data insights and being liaison between engineers and business partners.Own backtesting and experiments for fraud rules and models
#LI-REMOTE#LI-WISHXDS
Qualifications
Master’s degree in Statistics, or a quantitative field. PhD preferred.1+ years of work experience in finance/business/risk data analysis.Proficiency in SQL or other query languages, deep experience and strengths to develop complex queries.Development experience in at least one scripting language (R, Python, PHP, Perl, etc.).Strong analytical and problem-solving skills; ability to transform data into business insights and actionable recommendations. Experience working with large data sets that are structured and partially structured.
Preferred Qualifications:
1+ years of work experience in machine learning 1+ years years with big data systems, such as Spark, Hadoop 
Additional Information
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.