Matthew Phillips Email & Phone Number

San Francisco, California, US

• Using change data capture events from a database, set up streaming data pipeline to our feature store to reduce system latency.

San Francisco, California, US

• Closely partner with data science to architect and lead development of customer-facing ML services and the ML platform, which includes a feature store and related backend services.
• Architect and lead revamped MLOps pipeline on Vertex AI for key ML models in production, increasing reliability and reducing time to value from days to hours.
• Hire, manage, and mentor a team of three MLOps engineers of different levels.
• Own $700k/year data and ML platform budget, taking cost cutting measures while maintaining developer productivity. Lead company-wide migration to a new data warehouse and cost optimization efforts resulting in savings.
• Onboard dbt and decentralize the creation and maintenance of production analytics tables.
• Improve data infrastructure by introducing data quality checks and better monitoring and alerting of data pipelines.

San Francisco, CA, US

• Establish the data engineering team; hire, lead, mentor, and manage a team of six MLOps and data engineers.
• Bootstrap cross-functional MLOps team to improve data scientist productivity and robustness of ML model deployments.
• Lead initiative to replace a third-party data science platform with an in-house Kubernetes-based platform.
• Overhaul existing reporting data stack to use a modern data stack of Fivetran, Airflow, Snowflake, and Looker. Migrated reporting to Snowflake and achieved upwards of 200% increase in dashboard query performance.
• Engineered new method of measuring impact of product features on key metrics by parsing application logs, which became the authoritative source for Operations and Product reporting.

San Francisco, California, US

• Built data science platform on AWS to enhance productivity of dozens of data scientists using infrastructure as code tools CloudFormation and Terraform.
• Deployed batch and realtime machine learning models with Docker, Flask, and AWS SageMaker, including SoFi's first customer-facing ML model: a credit risk scoring model which increased quality loan applicant volume by.
• Leveraged model interpretability techniques for machine learning in credit risk scoring.
• Built data pipelines on TBs of data to populate enterprise data lake using AWS Glue and Athena.
• Maintained enterprise-wide Kafka infrastructure.

San Francisco, California, US

• As SoFi's second data scientist, I was both a hands-on machine learning engineer and modeler on various projects across marketing, operations, and credit teams.
• Developed machine learning model to improve prospect targeting, beating industry metrics by 10%.
• Developed and delivered training sessions on various topics in machine learning concepts (deep learning) and tools (Spark, Keras) to the analytics team.
• Reimplemented pricing algorithm in PySpark for individualized messaging to prospects.
• Built predictive targeting models using Spark ML on TBs of data to support marketing initiatives.

New York, NY, US

• Lead instructor for Part-time Data Science Immersive.

Santa Clara, CA, US

• Modeled topics and classified tens of thousands of documents of conversational text using latent Dirichlet allocation and random forest in scikit-learn.
• Built a credit scoring model for early stage venture lending using regularized GLMs.
• Worked with key stakeholders to identify data science projects and grow the data science internship program to more than 5 interns.

West Haven, CT, US

• Topics included maximum likelihood estimation and computational methods.

Arlington, Virginia, US

Education record

Master Of Science (M.S.), Data Science

Master Of Arts (M.A.), Economics

Bachelor Of Arts (B.A.), Political Science