1898 Merit Scholarship Recipient

-Developing major regulatory and financial reports in SQL Snowflake; consumers include state-level DGEs (Divisions of Gaming Enforcement), tribal and casino partners-Working with major marketing partners (notable partners include ESPN and CBS Sports) to deliver metrics on partnership performance (including but not limited to attributed customer registrations and first time deposits)-Employing Apache-Airflow to run scheduled ingestion (both Kafka and API endpoints), ETL and reporting jobs-Creating directed acyclic graphs (DAGs) in Python-Ingesting data from multifarious sources: AppsFlyer’s data locker, NeoGames (William Hill’s player management system) and Betting Engine (William Hill’s sports betting data layer)

-Assumed all previous responsibilities-Served as the data analysis team scrum master (a Kanban team)-Bridged communication between platform development teams and our analytics team-Illustrated and documented the intricacies of data instruction logic required to load Epic (an agency management system) users to the platform -Primarily instructed offshore developer teams as to how they should design the automated platform interface for Epic servicing roles, Epic transaction codes and Sagitta transaction codes-Developed a process to automate the platform validation component of my job (used novel SQL queries and Apache-Groovy instructions to write numerical data to our broker division mapping files)

-Managing the data load of various insurance agency management systems (including but not limited to Sagitta, AMS360, Epic and TAM)-Executing numerical RiskMatch platform validations for insurance brokers and agencies (many of whom gross more than $1 billion in premium annually)-Managing ETL (extraction, transformation and load) processes (checking extract logs/json failure messages to QA code and tracking data flow issues for RiskMatch platform auditing)-Stages in this ETL process: data review (data extracted from the given broker agency management system), canonical xml (assembler filtered data), ETL analyzers (SQL views of policy and transaction data as governed by RiskMatch platform rules), operational data storage (used for data source-independent reporting and then applied to our Redshift Warehouse), document object models (our programming API)-Building assemblers from scratch (designing SQL components to load data for policies, transactions, agency/broker users, lines of business, products and client information; instructing data load through Apache-Groovy, a Java machine language)-Writing data quality reports in SQL (downloadable Excel files used by RiskMatch platform users to maintain data quality in their agency management systems)-Pipelining data migrations for brokers (i.e. a broker wants to use a different agency management system; this requires linking predecessor policies to contemporaries, coding in cutoff dates on old systems, closing those systems and pointing the progenitor to its active child)-Anonymizing and cleaning our AWS Redshift warehouse data for conferment with customers (e.g. Travelers Insurance) -Managing the data analytics team's broker division mapping alerts (broker division mapping exists on the RiskMatch platform to highlight the structure of an agency or broker; I have to account for changes in customer organizational structure)

-Performed comparative product analysis for medication adherence products on the market-Aided in the design of a computer interface for the web based application of MATI's specially designed pill bottle (integrated with scale weighting mechanism and image processing)

-Tutored undergraduate student-athletes in engineering coursework (linear algebra, mechanics, dynamic system modeling and differential equations), statistics, calculus, microeconomics and macroeconomics

-Designed a dashboard for data collection on different sites for the product-Created visualization tools to better express statistical data