Greater Chicago Area
Analytics and data engineering leader with experience in multiple industries spanning advertising, customer science, and healthcare Cloud Platforms: AWS (Redshift, RDS, Lambda, ECS, ECR, EC2, EMR, S3, SNS, SES, Comprehend, SageMaker, Athena, Glue), Azure (Blob Storage, Functions, Synapse, Container Registry, Container Instances), GCP (Cloud Storage, Cloud Functions, Artifact Registry, BigQuery, Cloud Run, Dataproc, Pub/Sub, Eventarc, Vertex AI) Programming & Scripting: Python, SQL (Postgres, T-SQL, PL/SQL, HiveQL), Unix Shell, Jupyter Machine Learning & Data Science: Feature Engineering, Time Series Forecasting, Classification & Regression (Linear, Decision Tree, Neural Net), MLflow, Scikit-Learn, TensorFlow, PyTorch, XGBoost, NLP, BERT Big Data Platforms & Data Engineering: Airflow, Hadoop, Spark, Iceberg, Parquet, Snowflake, Databricks, DBT, Jinja, Docker, Jenkins, GitHub, Terraform Visualization & Reporting: Tableau, Power BI, Plotly, Seaborn, Matplotlib, Datorama, SAP Business Objects
● Serve as head of analytics and design, build, and scale the analytics and engineering practices for the $600 million total contract value Walgreens & Walgreens Health business ● Build a modern advanced analytics and engineering practice from the ground up using engineering and data science best practices with a focus on open-source tools/libraries, cloud architecture, automation, and productionization of machine learning systems ● Build a cross functional analytics team of 12 direct reports including Directors, Associate Directors, and Analysts spanning analytics, data science, and engineering ● Transform, analyze, model, and project data using supervised machine learning regression/classification, and artificial neural network classification leveraging Python and SQL to drive insights for reporting, predictive analytics, audience creation, MTA, personalization, performance/revenue forecasting, planning, and campaign optimization ● Productionize, parallelize, and automate machine learning models for real time predictions and automatic retraining using Python, Docker, AWS (EventBridge, SNS, S3, Lambda, ECR, ECS, and Redshift) ● Design and build modern ETLs and an analytics data warehouse leveraging Apache Airflow and AWS (S3, Lambda, ECS Fargate, Redshift) to support analytics activities ● Derive actionable insights from 1st party and 3rd party data to create a unified narrative for both technical and non-technical audiences ● Create analytics, engineering, and technology roadmaps that work in unison with account objectives, testing frameworks, and KPIs ● Develop and pitch new analytics and engineering products to clients to expand existing partnerships and integration with client business practices
● Design, build, and scale the analytics, engineering, and data platform vision, strategy, and SDLC from the ground up for the United States Army ● Build and scale the analytics practice, including 3 direct, matrix, and consulting reports, to support the $4 billion total contract value United States Army account ● Upscale business partner practices to improve their data fluency and analytics capabilities ● Serve as a principal authority for Army analytics and develop data governance and data privacy guidelines ● Transform, analyze, model, and project data using supervised machine learning regression/classification, and unsupervised clustering leveraging Python and SQL to drive insights for reporting, predictive analytics, segmentation, personalization, performance forecasting, and campaign optimization across direct marketing activities ● Modernize and fundamentally transform the analytics practice by designing, building, and owning core analytics products and data pipelines, leveraging AWS (S3, EC2, Lambda, RDS, Redshift, Glue, EMR, Comprehend) and Apache (Hadoop, Spark, Hive, YARN, Airflow) for advanced analytics, machine learning, modeling, and data parallelization ● Productionize, parallelize, and automate machine learning models for real time predictions and automatic retraining using Python, Docker, AWS (EventBridge, SNS, S3, Lambda, ECR, ECS, and Redshift) ● Implement engineering best practices for the analytics team, including data model and dictionary standardization, JIRA/Kanban to manage workstreams, adoption of Jupyter Notebooks, and Git for version control ● Visualize data using Python, Tableau, Datorama, and Adobe Analytics ● Lead data acquisition strategies and programs aimed at integrating disparate data sets ● Develop new data collection mechanisms and data pipelines ● Define analytics workstreams and facilitate collaboration and data sharing across 9 partner agencies within Omnicom Group
● Develop and optimize global company standards for the implementation of marketing analytics solutions ● Own the end-to-end delivery of CRM analytics projects with a total contract value of over $10 million for McDonald's Corporation ● Serve as promotion analytics subject matter expert for account and sales teams ● Organize and lead data explorations with clients to develop data readiness assessments and identify potential gaps and risks ● Develop responsibility assignment matrices and manage work streams for global cross-functional teams composed of internal, client, and vendor resources to ensure successful and continuous delivery of analytic solutions to clients ● Leverage and adapt existing company capabilities to create new solutions to fit unique client business needs ● Integrate teams and workflows gained through acquisitions into the current team structure ● Build, manage, and support custom petabyte scale data solutions leveraging AWS Redshift ● Build and manage Apache MapReduce ecosystem (Hadoop, Spark, Hive, YARN, Airflow) configured on AWS EC2 instances utilizing AWS EMR for petabyte scale advanced analytics ● Productionize, parallelize, and automate machine learning models for real time predictions and automatic retraining using Python, Docker, AWS (EventBridge, SNS, S3, Lambda, ECR, ECS, and Redshift) ● Transform, analyze, model, and project data using SQL, Python, supervised machine learning regression and classification to drive customer insights, performance forecasting, and promotional ad targeting ● Design and build ETL processes to create new data pipelines ● Train the data science team in the application of Jupyter, PySpark, SparkR, and supervised machine learning methods ● Develop and maintain operational and leadership level relationships with clients
● Direct the end-to-end delivery of SaaS behavioral analytics solutions using agile methodologies ● Own the technical delivery and maintenance for a suite of analytics projects with an annual contract value of $8 million for United Health Group Inc ● Develop responsibility assignment matrices for cross-functional teams to ensure successful and continuous delivery of analytic solutions to clients ● Translate client business needs into functional requirements ● Manage stateside cross-functional teams of up to 10 people in the development of custom product implementations ● Coordinate product releases across multiple internal and external teams ● Develop and maintain operational and leadership level relationships with clients ● Provide technical subject matter expertise to the sales team ● Develop and maintain KPIs and SLAs