Senior Data Scientist
WePay is looking for an exceptional data scientist to add to their machine learning team to detect payment fraud and merchant risk. This role will contribute heavily to WePay’s risk management value proposition and competitive advantage.
WePay is a fast-growing payments company that has built its API specifically for platform businesses like marketplaces, crowd-funding sites and small business software. Through this API, WePay allows platforms to easily offer payments to their buyers and sellers. WePay uniquely offers platforms a customized user experience while shielding them from fraud risk.
WePay’s proprietary risk technology leverages alternate data sources such as social media, platform data, and traditional business data to detect and mitigate fraud. You will find a highly data-rich environment and powerful risk data architecture from which to build machine learning systems.
- Build machine learning systems and models for detecting payment fraud, merchant fraud, and merchant risk
- Extract information like Entities, Entity Relationships and Events from large bodies of Text using various Text Mining and NLP Techniques
- Design and Implement Knowledge graph capturing information from various 3rd party/partner data sources and relationships therein
- Drive the complete lifecycle from data extraction through model deployment and evaluation
- Collaborate closely with engineering and risk teams
3+ years experience in applied machine learning / model development
2+ years experience in Text Mining and NLP domains.
Strong Practical experience with various Text Mining/NLP techniques like CRFs, HMMs, Entity Extraction, Relationship Extraction, Sentiment Analysis, Text Classification, Clustering, Similarity analysis, Active Learning etc.
In-depth understanding of machine learning and modeling algorithms such as decision trees, random forest, neural networks, Graphical Models, SVM, etc.
Technical expertise in data extraction, data scrubbing, feature extraction, model building / training, and statistical analysis
Proficiency in databases (SQL, NoSQL), statistical tools (R, SAS, etc), and programming languages (at least one of following: Python, Ruby, Java, etc)
M.S. or Ph.D. in a relevant technical field (computer science, engineering, physics, mathematics, statistics, etc.)
Collaborative, team player who drives to resolving customer needs
Outstanding track record of innovation and success