Senior Data Scientist

Job Description

Senior Data Scientist- TrustSafetyBangaloreTechnology Data ScienceFull Time EmployeeSwiggy started in 2014 with just a few restaurants on board limited to Koramangala in Bangalore,Swiggyis now India s leading food ordering and delivery platform. We recently received our series H round of funding and were able to raise an astounding $1 Billion.We have grown beyond our wildest imaginations. Starting off with just 2 neighborhoods in Bangalore, we are now present in over 240 locations PAN India and are only looking to grow further. More than 121,000 restaurant partners leverage Swiggy to reach new customers and increase their sales. All of this has been made possible only because of our motivated work force nearing 10000+ employees that run the show from start to finish.Every order delivered bySwiggy s fleet of over 1,50,000 Delivery Executives, the largest in India, ensures a host of customer-centric features, while ensuring we provide unparalleled conveniencefor our customersThe TS team acts as guardians of all our Users- Customers, Restaurant partners and Delivery partners at SwiggyApart from Data Science and Analytics; the team spans Audit Compliance leaders, business leaders, risk analysts, rockstar engineers, experienced architects, energetic product managers.As Senior member of Data Science for TnS, you will be responsible for conceptualizing new frameworks of identifying fraud and build world-class centralized fraud detection that provides a fraud score for all edges on the swiggy network, including customers, delivery executives, vendors and the interactions between themYou will work closely with stakeholders through the lifecycle of solution development, model deployment and future maintenance/ improvementMentor a small team of Data scientistsResponsibilities:-You will be responsible to drive the AI/ML initiatives on User Trust and Fraud prevention as well as overall SafetyCollaborate with engineering and design to define an ambitious strategy, develop and maintain a prioritized product backlog, and execute on itCome up with multiple hypotheses based on data and drive experiments collaborating with Engg, Product, Analytics; as well as test the validity of hypothesis with sound statistical methodologiesManage and own the entire end-to-end lifecycle of designing models, working with Engineering for implementation, to maintenance and enforcementDevelop a deep behavioral understanding and intuition of our vendors, customers and delivery executives, especially in the space of how they would violate our policies and game our systemsTranslate these intuitions into actionable, creative insights that produces heuristic or classification models to identify and take down those who violate our Terms of ServicesExplore and analyse multiple data sources related to deliveries, drivers and transactions to uncover signals related to fraudulent activity on the platformDevelop and maintain machine learning behavioural models to detect fraudulent behavioursBuild and deploy scalable machine learning models to enable our fraud, risk and safety systems.What are we looking forGood understanding of the fraud space with hands-on knowledge of fraud, payments and risk, especially on tech products and deep data understanding and curiosity driving continuous explorations for potential fraudulent use casesRecent programming experience in a production environment deploying models where inference latency requirement is millisecondsAdvanced data science skills, recognised experience in applied statistics and machine learning / data mining toolsGood to have working understanding of anomaly detection algorithms on 100 GB+ dataExperience in mentoring/ owning work for a small team of data scientists, preferably in a startup or a tech companyExperience in interfacing with other teams and departments to deliver impact solutions for organisationSelf-motivated, independent learner, and enjoy sharing knowledge with team membersDetail-oriented and efficient time manager in a dynamic and fast-paced working environmentExperience in Scala or PySpark on distributed systems,

Keyskills :
machinelearning analytics sql datamining datascience frauddetection auditcompliance fraudprevention creativeinsights anomalydetection positionmanagement lg ithms acledba itemresponsethe distribu