Tealium, San Diego, California
Dec 2020 – Present
Data Science Manager
Dec 2020 – Present
- Lead design and development of 2 flagship MLaaS product offerings for real-time ML inference.
- Collaborated with Staff Architects, SDEs, Data Engineers and Product to build real-time ML scoring engine scalable to handle 3B events per day.
- Built infrastructure for data scientist exploration and experimentation using anonymized customer data handling data across various verticals.
- Innovated real-time fraud and bot detection ML product using biometric and browser-level data.
- Oversaw enhancements to autoML propensity modeling product.
- Brought ML best practice standards to the company nascent in the journey implementing ML into its SaaS product suite.
- Coordinated with VP, and SVP, and C-level executives to build products that match the company vision
- Collaborated with Staff Architect to bring Databricks (on AWS) to the company to streamline ML and Big Data product development and improve time-to-market.
- Coordinated with data privacy and legal to ensure forward-thinking development of ML products that follow GDPR guidelines.
- Hired, and mentored Sr Data Scientists to be code owners of ML products.
- Built internal experimentation framework using dockerized instances ensuring uniform development environments across local and Databricks settings.
- Drove patent process for novel processing and data input handling for ensemble asynchronous real-time scoring engine utilizing DL and traditional ML techniques.