• Provide technical account support for companies mainly in the Automotive and Manufacturing verticals, as well as additional technical support for various accounts throughout enterprise, mid-market and commerical.• Evangelize the Databricks platform and present various demos and technical deep dives, hold office hours and coding sessions, and lead workshops for customers and prospects.• Spearheaded the internal Apache Spark and Databricks Data Engineering certification program for newly hired SAs/anyone else who wanted deeper technical knowledge on Spark programming. • Focused on teaching and mentoring both coworkers and customers alike, and helped out the internal technical enablement team and external training teams review trainings and provide feedback.

• Worked for the MapR Technologies Professional Services team. Responsiblities included: • traveling to MapR clients and helping them implement use cases using the MapR Platform• writing software in Scala, Java and Python to utilize technologies such as Apache Spark, MapR Streams/Kafka, MapR-DB/HBase, and Docker• helping with cluster adminstration on top of both on-prem and cloud-based MapR clusters• improving documentation and training materials, and writing technical blogs and internal wikisSome noteable projects:• created a credit and debit card fraud detection real time steaming analysis system pipeline and translated single noded python models into distributed spark ml models to flag fraudulent transactions and reverse charges within 5 minutes• fixed architecture of data lake and tables, improved overall performance of read writes, balanced out services across cluster nodes• updated and installed MapR distributions and fixed very deep and technical bugs from improper configurations and interactions between faulty services• installed our Data Science Refinery which leveraged Livy, Docker images, and Zeppelin Notebook to enable more user-friendly and deployable data science on the MapR platform

• Worked with data scientists to mine commute patterns, dwell time, and unsafe braking events using vehicle modem and telematics data using PySpark.• Created document clustering Scala Jars in Spark, improving NLP classifiers for vehicle recall prediction.• Led QA team for Ford Sales’ SAS data analytics platform for scoring customer likelihood to buy new vehicles.• Developed web app and REST API in React Redux/Spring Java/Spark for vehicle engineers to find, filter, reaggregate, and direct download large-scale telematics data; eliminated manual Hive queries for 90% of cases.

• Spearheaded company-wide pilot to upgrade manual Excel reports to dynamic Tableau visualizations; the successful pilot led to a $2MM initial investment to utilize Tableau for all future discovery analytics projects.• Led a team of 6 developers and analysts to create a customer-behavior research platform for electric vehicles and hybrids, based on data streamed from Ford Sync to the Hadoop environment, to help guide engineering development of EVs.

• Designed Ford’s process to automatically generate consumer-facing marketing assets on global Ford websites. This involved mapping part functions into marketing text and media to be curated on custom website templates; it yielded more accurate vehicle/trim descriptions, author rights management, and projected savings of $1MM/year in labor costs.

• Signed NDA. Created process plans using for food automation seed stage startup. Tested recipe variations and collaborated with robotics engineers to optimize for manufacturability/speed.

• Led a crisis-recovery team in a high-profile safety issue affecting the Dodge Dart’s release. Using insights derived from statistical data mining and testing, the plant enacted an effective stopgap solution and initiated a redesign to correct the issue, saving $250k/day. My contributions were personally recognized by the Senior VP of Quality.• Managed Six Sigma Black Belt projects for Jeep’s door assembly processes, involving multivariate testing/DOE and machine redesigns, including a door hinge attachment process that fixed a serious defect affecting over 50,000 vehicles.• Helped coach other coworkers to complete projects for Green Belt certification and assisted with PCA and statistical analysis.

• Oversaw manufacturing quality and engineering production specifications of $5MM portfolio of turbine blade castings.• Completed Root Cause Analysis of complex 15-year recurrent scrap issues ($50K/wk) throughout Alcoa’s supply chain.• Used Minitab to analyze data from design of experiment and ANOVA studies, and programmed in Excel VBA to automate data tasks such as flagging missing part numbers, update tracking info, color-code issue severity, etc.

Taught "Linear Statistical Models" and "Intro to Markov Chain Processes"