Jose Zenteno
Data & AI Leader
Lewisburg, PA
About Me
Visionary Data & AI Leader with over 13 years of experience steering enterprise data and AI transformation, target architecture roadmaps, and multi-million dollar data product strategies across Fortune 500 enterprises. Proven track record driving organizational evolution by establishing self-service, cloud-native architectural standards, declarative frameworks, and robust AI governance.
Setting the execution pace for cross-functional data science and engineering teams to accelerate time-to-market for real-time streaming pipelines and Agentic AI platforms. Combines executive leadership with a passion for talent development as an Adjunct Professor at Bucknell and Marquette Universities, actively mentoring and preparing a future-ready technical workforce.
Professional Experience
FEDERAL EXPRESS
Manager, Data Science
May 2023 – Present- Establishing strategic vision, target architectural standards, and execution velocity for enterprise Data and AI initiatives; leading cross-functional engineering organizations to deliver scalable cloud platforms and over $100M+ in realized business value.
- Influenced data and AI practitioners to adopt Google Cloud Platform (GCP) by championing adoption and education frameworks, empowering engineering teams with target architecture strategies, and establishing scalable governance frameworks to accelerate cloud-native transformation.
- Partnered with InfoSec, IT, and delivery teams to govern and deploy Gemini Enterprise capabilities across the organization, expanding AI-driven general productivity and establishing an enterprise AI portal to accelerate cross-functional AI adoption.
- Defined and governed standardized streaming and batch ingestion frameworks across the Data Foundation to accelerate cloud adoption; enabled distributed engineering teams to securely deploy AI-ready pipelines via declarative YAML/SQL configurations, reducing operational engineering overhead by 90%.
- Architected an enterprise-grade Multi-Agent System (MAS) leveraging Gemini APIs and Google's Agent Development Kit (ADK) to automate cost governance. The platform continuously monitors BigQuery Information Schema logs, applying context-aware SQL optimizations that unlocked $880K in savings during week one with an anticipated 7-8-figure annual cost reduction.
- Spearheaded the architectural blueprint and operational standards for a real-time streaming platform using the Apache Beam Python SDK. Formulated an asynchronous surge-absorption architecture via Pub/Sub, stateful Dataflow deduplication workers, and sub-millisecond Bigtable lookups to serve denormalized BigQuery wide tables for immediate AI consumption at a $75/day run rate.
- Championed a tiered vision architecture using a lightweight, open-weight model to evaluate peak loads of nearly 300 images per second at sub-second latency. Set governance guidelines to intelligently route only 5% of edge photos to Gemini for advanced classification, reducing frontier API expenditure by $1.8M annually while auditing 6–10M daily delivery photos—driving a 12% drop in delivery disputes and saving $1.4M in vendor operational costs.
- Uncovered a critical telemetry software defect and spearheaded forensic analysis linking corrupted data to downstream ML models and APIs. Presented tactical remediation strategies to senior leadership, driving cross-functional alignment for a global hot-fix that preserved $30M in recurring annual revenue across major accounts (Walmart, Best Buy, Chewy).
Core Tech Stack: GCP, BigQuery, Gemini Enterprise, Google ADK, Multi-Agent Systems (MAS), Apache Beam, Dataflow, Pub/Sub, Bigtable, Cloud Run, YAML/SQL Declarative Orchestration, Open-Weight Vision Models, Python
Awards & Recognition
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Five Star Award (FY 2026): Honored with the FedEx Five Star Award, the company's highest individual and team honor, for exemplary leadership, technical vision, and cloud architecture delivery.
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Leadership Bravo Zulu Award (FY 2026): Awarded for leading post-incident forensics on scanner telemetry logic, safeguarding $30M in digital revenue.
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Global Security Culture Champion (FY 2024): Named sole global recipient for conceiving a last-mile risk management platform that alerted field leadership and security officers to compromised shipments—mitigating inventory loss and winning back a $100M+ shipper account.
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Two Purple Promise Quality Awards (FY 2024): Recognized for impact in guiding ML-driven PPOD audits and the enterprise $100M fraud and loss prevention framework.
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Five Star Award (FY 2023): Received the FedEx Five Star Award for architecting solutions that eliminated $3M in annual contractor overpayments.
Academic Experience
Bucknell University
Instructor, ANOP 242: Data Analytics - SQL, Cloud, AI
Curriculum & Industry Focus
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Taught fundamental and advanced database concepts, including relational database design, data integrity, and complex SQL programming (joins, subqueries, and window functions).
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Pioneered the intersection of Generative AI and data analytics by teaching students to leverage LLMs and Gemini for SQL generation, sentiment analysis, entity extraction, and data enrichment within Google BigQuery.
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Aligned academic coursework directly with industry standards by integrating the Google Cloud Data Analytics Professional Certificate into the curriculum, giving students hands-on experience with cloud data warehousing.
93%
Effective Instruction
"His material is highly relevant to the workforce today. He is an approachable, hard-working, and considerate professor who brings unique industry expertise."
Marquette University
Instructor, ECON 6118-701: Introduction to Python
Curriculum & Industry Focus
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Instructed students in core Python programming, object-oriented concepts, and essential data structures via a cloud-based Jupyter Notebook environment.
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Focused heavily on industry-standard data science workflows, utilizing the Pandas library for complex data manipulation, cleaning, missing value treatment, and merging DataFrames.
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Guided students through full-lifecycle data projects, from Exploratory Data Analysis (EDA) and accessing web APIs/databases, to building predictive classification and regression models using Scikit-Learn.
~91%
Effective Instruction
"This class was a great introduction to how AI agents operate and how to implement them in a real-world setting. The examples were fun to see and were engaging."
Academic Leadership & Talent Development
Beyond enterprise corporate leadership, I am deeply committed to shaping the next generation of technical talent. As an Adjunct Professor at Bucknell University, I design hands-on curricula integrating Google Cloud Data and AI tools, BigQuery GenAI pipelines, and modern cloud analytics. At Marquette University, I teach industry-standard Python data science workflows and Pandas data manipulation. Previously, as Lead Computer Science Instructor at Nucamp Bootcamp, I mentored and upskilled over 200 professionals in Python backend development, database programming, and automated data pipelines.
Prior Experience
FISCAL AND ECONOMIC RESEARCH CENTER
Research Analyst
March 2013 – May 2016- Developed multivariate regression models regarding rural broadband deployment; findings guided state funding allocations and were featured in The Wall Street Journal.
Core Tech Stack: Econometric Modeling, Multivariate Regression, Statistical Analysis
NORTHWESTERN MUTUAL
Analytics and Research Consultant
May 2016 – Sept 2018- Served as primary analytical lead to optimize a multi-million dollar financial training budget; built Tableau and Power BI systems to guide business change management.
Core Tech Stack: Tableau, Power BI, Budget Optimization, Business Change Management
NESTLÉ USA
Sr. Data Scientist
May 2020 – May 2021- Guided engineering teams and internal data engineers in architecting Nestlé's end-to-end enterprise insights data warehouse utilizing Databricks and Power BI.
- Partnered with business leaders across Supply Chain, Sales, and HR to deploy scalable data-driven behavioral analytics, driving multi-department operational efficiency.
Core Tech Stack: Databricks, Power BI, Advanced Behavioral Analytics, Data Warehousing
FEDERAL EXPRESS
Data Scientist
Sept 2018 – May 2020- Engineered an automated, self-service data ingestion framework to pull from legacy core servers. Led technical workshops that accelerated cross-organizational cloud adoption and pipeline modernization.
- Directed on-premise to cloud data migrations using a custom cross-cloud integration framework. Modernized enterprise analytics by replacing legacy daily SAS reports with dynamic, near real-time dashboards.
Core Tech Stack: Cloud Data Warehousing, Data Ingestion Frameworks, Modernization, Real-time BI, SQL
Sr. Data Scientist
May 2021 – May 2023- Engineered a proactive anomaly detection platform to identify and mitigate package fraud. Designed pipelines triggering targeted field actions, averting an estimated $100M in annual revenue losses.
- Led the Pick-up & Delivery data science team, delivering 8 enterprise data products in FY2023. Co-architected a self-service P&D data warehouse scaling to over 18 billion records, empowering 100+ product features that enhanced driver visibility.
- Mined big data telemetry to isolate a critical scanner software anomaly responsible for contractor overpayments. Partnered with IT, Finance, and Legal teams to drive remediation, permanently closing the process gap and reclaiming $3M in annual savings.
Core Tech Stack: Python, Big Data Telemetry, Data Warehousing, Anomaly Detection, Enterprise Risk Mitigation
NUCAMP BOOTCAMP
Computer Science & Analytics Instructor
Jan 2020 – Dec 2023- Upskilled 200+ professionals in Python backend development, automated data pipelines, and SQL programming. Maintained an instructor rating of 4.8 / 5.0.
Core Tech Stack: Python, SQL, Automated Data Pipelines, Backend Engineering
Education
Marquette University
Master of Science, Applied Economics
Completed
GPA: 3.5 / 4.0
University of Wisconsin - Whitewater
Bachelor of Business Administration, Economics - Summa Cum Laude
Completed
GPA: 3.86 / 4.0