John Gilman
San Francisco,CA
Summary
Expert in ML ops, data modeling, data engineering, data warehousing, data analysis, and data visualization. Proven leader in creating scalable, secure, and cost-effective data architectures that meet the business needs and goals of the organization.
Overview
10
10
years of professional experience
Work History
Data Science Consultant
Independent
04.2022 - Current
- For Meta, provided data science consulting to the Privacy Compliance Group for Meta's FTC consent order
- Built various surveillance tools to monitor compliance.
Dir of Data
Pill Club
04.2019 - 03.2022
- Built an NLU language model utilizing neural transformers to classify clinical content in patient SMS messages and route them to the appropriate queue
- Built a marketing lead scoring model utilizing LightGBM
- Designed and led the building of an AWS hosted data infrastructure, including the data integration of 20+ platforms into a data lake and data warehouse, utilizing the Matillion ELT platform.
Sr. Dir. Data Science
SoFi
08.2017 - 04.2019
- Built data science team for the Marketing Analytics division of SoFi
- Utilized deep learning with an autoencoder/GAN hybrid on Tensorflow to classify high dimensional data for market segmentation and audience targeting
- Model helped to significantly reduce advertising costs while maintaining a high level of conversions
- Employed machine learning for cross-sell, underwriting, and pricing.
Head of Data
Integral
05.2013 - 08.2017
- For a high frequency FX exchange, founded the data science team and served as chief data architect and machine learning specialist
- Built an FX analytics platform (an industry first) for large bank customers such as Wells Fargo, Mizuho, and AxiCorp to analyze real-time and historical trade executions of up to three years while maintaining millisecond-level resolution on 24PB of data
Education
Bachelor of Science - Information Technology
SUNY At Albany
Albany, NY05.2004
Skills
- MACHINE LEARNING: Transformers for NLU, variational autoencoders, generative adversarial networks, gradient boosted trees, convolutional neural nets
- MACHINE LEARNING FRAMEWORKS: PyTorch, Tensorflow/Keras,
- CLOUD: AWS RDS, Redshift, DMS, Kinesis, Glue, Athena, Comprehend
- CLUSTER: PySpark, AWS EMR, AWS SageMaker
- CONTAINER: Docker/Kubernetes, AWS Fargate/EKS
- NOSQL: Cassandra, Mongo, DynamoDB
- LANGUAGES: Python/Pandas, Java, Scala, JavaScript
- MIDDLEWARE: Kafka, RabbitMQ
Timeline
Data Science Consultant
Independent
04.2022 - Current
Dir of Data
Pill Club
04.2019 - 03.2022
Sr. Dir. Data Science
SoFi
08.2017 - 04.2019
Head of Data
Integral
05.2013 - 08.2017
Bachelor of Science - Information Technology
SUNY At Albany