Lead Scientist
2017 - PRESENTVality- Developed and maintained a credit-and-fraud analysis pipeline.
- Wrote risk, compliance, portfolio management, and pricing policies.
- Built and supported a proprietary credit score system based on bureau, purchase, and social network data.
- Mapped and integrated data providers.
- Led teams.
Technologies: Amazon Web Services (AWS), TensorFlow, PythonData Scientist | Delivery Lead
2016 - 2017Capco- Developed and managed the delivery of analytics solutions for Bradesco's Next Bank; including project scoping, planning, reporting, and risk management.
- Led the development of a self-service help solution for Next Bank's mobile app. The model was based on TF-IDF information retrieval with feedback boosting using Thompson sampling.
- Managed the development of a spending limit recommendation solution for Next Bank's mobile app. The model was based on user-user collaborative filtering using account and credit card data with a linear regression model to handle a cold start.
- Led the development of a real-time offer recommendation solution for Next Bank's mobile app. The model had to track customer transactions in real-time to recommend personalized offers and perks based on customer preference and eligible partners.
Technologies: Gemfire, Solr, Pivotal Cloud Foundry (PCF), Hadoop, Apache Kafka, Apache Hive, Spark, PythonBig Data Scientist
2013 - 2016Chaordic- Researched and developed recommendation algorithms for eCommerce.
- Developed a real-time product recommendation service for cross-store advertisement. The model used a customer's list of current interests to recommend similar products that are cheaper in other online stores. The solution also included a design of an auction system for offer placement bidding.
- Built a real-time bidding system for advertisements in order to automate and increase the ROI for the advertiser. The model considered a customer's navigation and purchase history to estimate the optimal bid price.
- Created an experimentation platform to streamline the evaluation and deployment of A/B tests. The platform helped reduce—by half—the time and costs of conducting online experiments.
Technologies: Redis, Cassandra, Apache Kafka, Elasticsearch, Amazon S3 (AWS S3), Amazon EC2, Spark, Scala, Python