Deep Learning Engineer
2019 - PRESENTVoiceops- Developed the architecture and construction of AWS-based infrastructure for large-scale machine learning. VoiceOps is an AI-driven coaching and training platform for call-centers.
- Introduced and delivered models to support the transcription process. This included developing scripts to pre-train, fine-tune, and fully integrate transformers (e.g., BERT, various HuggingFace Transformers) into novel new architectures that included both text and statistical data.
- Built a modified transformer to automatically score the quality of transcriptions and determine whether they should pass to the client (ROC-AUC = 0.90).
- Created a modified transformer that automated the detection of speakers based on text (ROC-AUC = 0.97).
- Automated the estimation of how long a transcript would take to transcribe to replace a fixed-price system (cost savings of 20-30% of total transcription costs).
- Improved Automated Speech Recognition (ASR) via Seq2Seq architectures.
Technologies: Document Processing, Custom BERT, Data Scientist, Deep Learning, Amazon Web Services (AWS), PyTorch, Torch, Natural Language Processing (NLP), Pandas, Machine Learning, AWS, Python, Keras, Fairseq, Artificial Intelligence (AI)Chief Technology Officer
2019 - PRESENTMobilads- Constructed and optimized a geospatial system that maps physical ad impressions based on vehicle GPS data and mobile GPS data. The Mobilads geospatial system was successfully built to operate worldwide and built to scale to thousands of vehicles and billions of GPS points.
- Developed automated reporting systems for the clients of Mobilads to demonstrate the technology.
- Built up the company's IP portfolio through the integration of census, geotracking, and social data to enrich what Mobilad's knows about the people that see their vehicles. This ensures consistent industry-leading return on ad-spend.
- Architected and led the development of the Mobilads app for autonomously managing tens of thousands of drivers.
Technologies: Data Scientist, Amazon Web Services (AWS), Pandas, AWS, Shapely, GeoPandas, PythonFounder, CEO, Principal Consultant
2016 - PRESENTRelu Analytics- Consulted as the senior data scientist at Step Energy Services. Built algorithms for optimizing the use of fixed equipment (extended maintenance, failure prediction, forecasting, and budgeting), as well as cash flow prediction.
- Collaborated with the senior leadership team of Cinelytics to build scalable NLP pipelines. Provided code samples and walked through the software engineering team on building and deploying deep learning models in the capacity of a data scientist at Cinelytic.
- Designed an end-to-end machine learning application using Google Cloud to serve as an API for the front-end team in order to deliver predictions via the companies UI. Consulted as the data scientist at Meditalente GMBH.
- Consulted as the senior data scientist for a fixed project at MariaDB (non-disclosable).
Technologies: Document Processing, Custom BERT, Web Scraping, Data Scientist, Deep Learning, Amazon Web Services (AWS), PyTorch, Torch, Natural Language Processing (NLP), Pandas, Machine Learning, AWS, TensorFlow, Keras, Sklearn, Python, Artificial Intelligence (AI)CEO (Previously Chief Data Scientist)
2017 - 2019Sigmai- Led a team of 15 data scientists, linguists, software engineers, product managers, and sales professionals.
- Focused primarily on deep learning for text classification with Keras and Tensorflow, and its integration within a rule-based NLP system.
- Developed an out-of-memory document clustering system to allow the clustering of billions of news articles.
- Built a natural language processing (NLP) system that rivaled the best NLP companies in finance, and led to data trials with some of the largest fund managers.
- Led and oversaw the Newsful application (app.Newsful.io) that was shortlisted for the 2018 SIIA CODiE Award. The business operations were acquired by Commetric (https://commetric.com).
Technologies: Document Processing, Custom BERT, Data Scientist, Deep Learning, Amazon Web Services (AWS), Torch, Natural Language Processing (NLP), Pandas, Machine Learning, AWS, R, TensorFlow, Keras, Python, Artificial Intelligence (AI)Contract Data Scientist
2017 - 2018Dreamtalents- Designed an end-to-end machine learning application using Google Cloud to serve as an API for the front end team.
- Matched candidates with businesses by utilizing staff demographic data, historical job data, and interview transcripts.
Technologies: Data Scientist, Pandas, Machine Learning, Google Cloud Platform (GCP), Python, Artificial Intelligence (AI)Data Scientist
2016 - 2018Zalando- Built analytical tools and ETL pipelines in Spark on AWS.
- Built predictive tools for targeting audiences for specific ad campaigns.
- Developed interactive data applications for product owners using Python and R (Shiny) to automate time-consuming analysis tasks (customer journeys, return on ad spend).
- Developed a system to optimize how ads are placed within the search and recommendation engine to reduce lost revenue due to poor ad placement by up to $0.5 million USD per month.
- Designed a system for determining the causal impact of multiple concurrent ad campaigns (off-site, on-site, banner Ads, and full-page ads) using regression and Bayesian time-series models.
Technologies: Amazon Web Services (AWS), Data Scientist, AWS, Pandas, Machine Learning, Sklearn, R, Spark, Python