Mick Nassar, Data Analysis Developer in Chicago, IL, United States
Mick Nassar

Data Analysis Developer in Chicago, IL, United States

Member since May 19, 2020
Mick is a seasoned developer with experience at a Fortune 100 company creating enterprise back-end API solutions, hands-on machine learning experience in multiple languages, a proven track record of creating products worth millions of dollars, and a patent pending. He loves what he does and he's good at it. Let him put his skills to work for you.
Mick is now available for hire

Portfolio

  • Cigna
    Splunk, data modeling
  • Express Scripts
    Apache Spark, Scala, Java, Hadoop, Zeppelin Notebook
  • Express Scripts
    Java, Pega PRPC, Oracle 12c Database, Oracle Advanced Queue, REST API

Experience

Location

Chicago, IL, United States

Availability

Full-time

Preferred Environment

MacOS, Linux, Spark, Scala, Python, Hadoop, Zeppelin Notebook

The most amazing...

...project I've deployed was called ICC. It's a streaming ML API worth $30 million to Cigna that ensures an insurance claim is billed correctly.

Employment

  • Machine Learning Engineer

    2019 - PRESENT
    Cigna
    • Engineered various improvements to my KNN model so the solution can identify insurance claims submitted to the incorrect benefit type with 99.8% accuracy overall in 3-5 seconds per claim.
    • Yielded the company about $30 million in savings every year with the laser-precision of the solution.
    • Created CLI scripts for auto restarting APIs, CLI applications for auto fetching logs from distributed databases, monitoring dashboards with Splunk enterprise, and more as needed.
    • Created design docs and schematics to submit with the company patent application for this product.
    • Began data exploration and modeling for a new NLP use case I pitched to management after the successful launch of ICC.
    Technologies: Splunk, data modeling
  • Machine Learning Engineer

    2018 - 2019
    Express Scripts
    • Curated the finest tools, processes, and best practices for development on the organization’s first ML team.
    • 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.
    • Tested various iterations of my model on different features, training data, and test data with Zeppelin notebook and as a jar on an internal Hadoop cluster to ensure optimal accuracy and that my solution was not overfitting.
    • Launched our production pilot to evaluate the performance of my new KNN model, the communication framework around it, and the accuracy of results. I implemented incremental improvements with feedback from our business stakeholders.
    Technologies: Apache Spark, Scala, Java, Hadoop, Zeppelin Notebook
  • Associate Software Engineer

    2017 - 2018
    Express Scripts
    • 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.
    • Designed and built new Pega applications that automate and manage the lifecycle of a specialty prescription. I got certified by Pegasystems as a systems architect.
    • 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 collaborated with the end-user experience team to improve productivity across the enterprise.
    Technologies: Java, Pega PRPC, Oracle 12c Database, Oracle Advanced Queue, REST API

Experience

  • Enterprise Eligibility API (Development)

    I created an enterprise API written in Java around a legacy product called Oracle Advanced Queue. It facilitates enterprise-wide patient eligibility searches to ensure that a patient has active insurance before dispensing specialty prescriptions.

  • Incorrect Claim Center (ICC) (Development)

    I created the ML model for a project called Incorrect Claim Center or ICC for short. Its purpose is to determine if a benefit type on a given insurance claim is correct before being submitted to the payer.

  • Adverse Events (AE) (Development)

    I'm currently creating the model for this ML project. The purpose of the adverse events use case, or AE for short, is to identify a potential adverse event being reported by a patient during a live phone call, document the event for reporting, and transfer them to a qualified clinician to prevent hospitalization or death if possible. This is a use case that I came up with and successfully pitched to management.

Skills

  • Languages

    Scala, SQL, Java, Python, JavaScript
  • Frameworks

    Apache Spark, Hadoop, Phoenix
  • Libraries/APIs

    PySpark, Pandas, Spark Streaming, Scikit-learn
  • Platforms

    Zeppelin, Apache Kafka
  • Other

    Machine Learning, Data Analysis, Bash Scripting, RESTful APIs, Natural Language Processing (NLP), Progressive Web Applications (PWA)
  • Tools

    PegaRULEs Process Commander (PRPC)
  • Paradigms

    Agile
  • Storage

    HBase, Apache Hive

Education

  • Courses in Mathematics
    2018 - 2019
    Harvard Extension School - Cambridge, MA, USA

Certifications

  • Data Science with Python
    DECEMBER 2018 - PRESENT
    Accelebrate
  • Certified System Architect
    NOVEMBER 2017 - PRESENT
    Pegasystems
  • Computer Science 101
    JANUARY 2017 - PRESENT
    LaunchCode

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