Vice President of Data Engineering

• Feb 2022 - Present

Our mission: To create the world's best AI platform for engineering & quality leaders. Engineering leaders are releasing vehicles & devices with new technologies faster than ever, but quality and other risks have never been worse, due to engineering challenges & supply chain. Axion's platform helps engineering leaders accelerate the pace of innovation while avoiding safety issues, recalls, and other risks. Our mission: To create the world's best AI platform for engineering & quality leaders. Engineering leaders are releasing vehicles & devices with new technologies faster than ever, but quality and other risks have never been worse, due to engineering challenges & supply chain. Axion's platform helps engineering leaders accelerate the pace of innovation while avoiding safety issues, recalls, and other risks.

Software Engineer

• Mar 2021 - Feb 2022

- Led a cross-functional team of 7 to a Microsoft Global Hackathon 2021 Challenge Win (over 70k participants total) - Spearheaded the effort to modernize the Federal Reporting platform by converting all infrastructure to IaC using Azure Bicep - Architected and implemented a solution that delivers and monitors over 130 controls within the Federal Business Intelligence solution to ensure that the platform is CMMC L3 compliant - Managed the development of a new CICD pipeline that reduced deployment times by over 50%. Show less

Senior Consultant – Data Engineering

• Nov 2020 - Feb 2021

- Lead DE on an internal product that is used to expedite analytics projects in the energy space by creating modular pipelines using the Kedro framework.- Created an automatic data profiler that uses the python library Greater Expectations to evaluate data quality on a variety of dimensions. System was extendable to allow for custom logic to take place when quality violations took place.

Data Engineering Consultant

• Dec 2019 - Nov 2020

Oil and Gas Client- Led a team of 3 data engineers to create full stack solution for a major oil client that generates $40M annually which involved using sensor data from a refinery as well as various services from the Azure Cloud (ADF, Blob Storage, Databricks/PySpark, App Services) to create an optimization model that provides recommendations to plant operators as to how they should run the plant at an hourly cadence.- Collaborated and created solution architectures for client technical leadership and presented sprint deliverables to the client management team during bi-weekly steering committee sessions.- Taught the client team about best practices when designing software solutions and helped them learn critical tools such as Git, python, and various Azure cloud services in order to ensure sustainability of the project.Mining Client- Created a data science model pipeline that predicts whether or not a critical mining component was going to fail within the current hour. The solution used was built in Google cloud using Composer, Cloud Functions, Airflow, and pandas. Impact delivered from the project resulted in $2M of annual savings.- Built out a data anomaly detection system which used ADTK and pandas to determine if the variances of critical sensors were drifting over time, indicating that we should retrain our data science model Show less

Data Engineer - Fellow

• Nov 2018 - Dec 2019

F100 Manufacturing Client- Created an advanced analytics pipeline using Kedro/Databricks/Docker that would predict the optimal line up of workers in order to increase remanufactured product throughput. Impact delivered from the project is $9M of recurring annual revenue.- Created a tool that would break down a remanufactured part into all of its subcomponents using the AnyTree Python library. This provided accounting a more concrete valuation of inventory as opposed methods used prior.

Senior Consultant – Data Engineering

• Nov 2018 - Feb 2021

Part of the advanced analytics group, QuantumBlack. Part of the advanced analytics group, QuantumBlack.

Data Engineer

• May 2018 - Nov 2018

• Created a real time sentiment analysis pipeline using Lambda/SQS that would ingest customer feedback and rank the positive/negative sentiment associated with the review. The system would then forward flagged reviews to relevant CSM representatives.• Built out a worker recommendation system using a combination of Lambda, SNS, DynamoDB, and a graph database.• Put a machine learning model into production that would provide the likelihood of a worker to pick up different positions. Show less

Business Intelligence Analyst

• Sep 2017 - May 2018

• Constructed an automated transaction based SQL model that used an activity log of CSM’s actions in conjunction with financial information to classify the profitability of clients.• Developed a worker churn model that ultimately led to the LTV of a customer cut by various verticals and positions.• Worked with the Data Science team to create a functional model of worker and position demand pools by location.

Finance & Statistics Tutor

• Jan 2017 - May 2017