Verified Expert in Engineering
Data Analysis Developer
Mick is a seasoned developer with experience at a Fortune 100 company creating real-time enterprise API solutions, machine learning implementations in multiple languages, and products worth millions of dollars with several patents pending. He loves what he does, and he's good at it. Let him put his skills to work for you.
Zeppelin, Hadoop, Python, Scala, Spark, MacOS
The most amazing...
...project I've created so far is called Adverse Events. It reads millions of rows of call data using NLP technology to identify when a patient reports an ADE!
Machine Learning Engineer
- Designed a Spark K-Means classifier running on Spark NLP embeddings generated from free text transcripts of phone calls to identify words indicative of an Adverse Event. This product will improve patient safety and expand an existing revenue stream.
- Applied PCA dimensionality reduction on NLP embeddings to visualize clusters generated and easily identify areas of focus without having to label data. This approach saved much time and manual work, enabling the use case to move expeditiously.
- Launched our pilot product and received an enthusiastic response. Out of about 2 million rows of transcript data, the solution returned about 5,000 words for review. In the first 19 calls reviewed a reportable AE was identified.
Machine Learning Engineer
- Crafted a binary KNN classifier in Scala with Hamming distance from a training set I translated into binary code. This improved processing time so the model could be used with a streaming solution and externalized spring API in real-time.
- Encountered a challenge at the end of the pilot as we discovered the current claim process didn't make enough features available when predictions needed to be invoked. We collaborated with the business, outlining the challenges and possible solutions.
- Wrote scripts for auto restarting APIs, auto fetching logs from distributed databases, monitoring dashboards with Splunk enterprise and more as needed. This laser precise solution will yield the company an estimated $29 million in savings every year.
Associate Software Engineer
- Created an enterprise API in Java around a legacy product called Oracle Advanced Queue. It facilitates enterprise wide patient eligibility searches, saving about $100,000 dollars every year. It was the biggest value added FY 2017 on the project.
- Built new Pega applications that automate and manage the lifecycle of a specialty prescription, including a payer selection system that maps an individual’s insurance information to corresponding claim centers with 95% accuracy.
- Solved a difficult problem that arose in an MVP1 production release that was impeding our entire project because users were unable to process payer information. I received recognition from my organization’s VP afterward.
- Authored many confluence pages to help our engineers, users, and business stakeholders understand our software. I also worked with the end user experience team to address technological barriers to innovation and improve productivity.
Adverse Events (AE)
Incorrect Claim Center (ICC)
Enterprise Eligibility API
Apache Spark, Hadoop, Phoenix
PySpark, REST APIs, Pandas, Spark Streaming, Scikit-learn, NumPy
RESTful Development, Agile
Zeppelin, Apache Kafka, MacOS, Linux, Pega, Oracle
Machine Learning, Data Analysis, Natural Language Processing (NLP), Progressive Web Applications (PWA), GPT, Generative Pre-trained Transformers (GPT), Data Modeling, Spark NLP, OAuth
PegaRULEs Process Commander (PRPC), Splunk, Confluence, Eclipse IDE, Grafana, IntelliJ IDEA, PyCharm
HBase, Apache Hive
Courses in Mathematics
Harvard Extension School - Cambridge, MA, USA
Data Science with Python
Certified System Architect
Computer Science 101