AI, ML, and Analytics Leadership

Strategic data science and AI leader with over a decade of experience driving enterprise-wide analytics, data platforms, and cross- functional innovation. Expert in aligning AI/ML—including LLMs and multi-agent systems—with business goals to deliver measurable impact and P&L growth.

Microsoft

Senior Data Scientist, Commercial Research & Insights Designed, developed, and advised on AI and analytical deliverables and strategy for the global multi-billion-dollar enterprise cloud- architecture deals that contributed to 30% growth in Azure Data & Copilot services and Connected Field Service Operations. Accomplishments:

Engineered and deployed AI and LLM-powered multi-agent systems to scope, model, and/or optimize commercial targeting strategies across Xbox, Copilot, and MS365, aligning AI-driven insights with executive goals to improve P&L performance. Championed the documentation and modernization of data architecture, database design, and AI requirements, integrating Databricks/Spark, Airflow, and MLflow to support multi-product MLOps at scale. Led user hold-out experimental design and causal inference modeling to evaluate the impact of AI-driven feature launches, directly informing product strategy and roadmap prioritization across multi-billion-dollar platforms. Tools/Frameworks: Python, R, SQL, Git, Fabric (datalake, data warehouse, data pipelines), Databricks, PyTorch, Keras, LangChain, Llama3,` Hugging Face, OpenAI, Azure, Flask, Streamlit, Windows, Linux, Virtual Machines March 2025 - Present

Senior Data & Applied Scientist, Chief Technology Office Headed all analytic and AI solutions for CSA’s Chief Technology Office, driving impact in software sales, tooling awareness, and sales AI-tool utilization.

Accomplishments:

Spearheaded Azure sales strategy and customer success initiatives that increased the utilization of the Chief Technology Office Global Standard Accelerator program by nearly 25%. Architected end-to-end data solutions using Azure ecosystems, improving data pipeline efficiency. Collaborated with cross-functional teams, influencing seller strategy and innovation that reshaped seller engagement, providing ongoing recommendations to preempt competitive advantages, while aligning with strategic business priorities. Tools/Frameworks: Python, R, SQL, Kusto, Git, Fabric (datalake, data warehouse, data pipelines), VS Code, OpenAI, PyTorch, Keras, TensorFlow, Scikit-Learn, Flask, Streamlit, Azure, Power BI, Windows, Linux, Virtual Machines, CI/CD Aug 2024 - Mar 2025

+1-832-***-**** · *******.*****@*****.*** · https://www.linkedin.com/in/leondrajames Indianapolis, IN, 46112

Leondra R. Gonzalez, MBA

PROFESSIONAL EXPERIENCE

AI & ML Strategy

Enterprise Data Architecture

LLMs & Multi-Agent Systems

Data Governance & Compliance

Marketing Science

Technical Leadership

Operations Research

Business Intelligence & Reporting

Experimentation Design & Statistics

KEY COMPETENCIES

AI & ML ENGINEERING LEADERSHIP

Senior Data & Applied Scientist, Cross Solution Areas GTM Designed, developed, and advised on AI and analytical deliverables and strategy for the global multi-billion-dollar enterprise cloud- architecture deals that contributed to 30% growth in Azure Data & AI services and Connected Field Service Operations. Accomplishments:

Championed AI and LLM-based propensity and sales blocked prediction models using embedding and RAG/CAG techniques to improve high-priority enterprise engagements and go-to-market targeting strategies. Implemented NLP machine learning tasks, including semantic textual similarity and summarization models that reduced manual feedback review time by over 40%.

Collaborated with data engineers to create executive reporting tools (IAP, XSA LxE) that influenced C-level decisions and resource allocation for strategic global accounts.

Tools/Frameworks: Python, R, SQL, Git, Kusto, VS Code, OpenAI, PyTorch, Keras, TensorFlow, Scikit-Learn, Azure, Power BI, Windows, CI/CD

Oct 2022 - Aug 2024

Senior (Technical) Analytical Program Manager, Marketing Science Managed offshore engineering and analytics team in the development of Bing and MSAN business performance reporting, KPIs, and predictive modeling.

Accomplishments:

Oversaw a team of 10 data scientists, analysts, and engineers to build and deploy enterprise machine learning models, data pipelines, and accessibility that improved the relevance and accuracy of search results, contributing to a 5% demand increase across 4 verticals.

Broadly set the vision as the technical scientific expert for Microsoft Advertising Sales Enablement by engaging with a broad range of stakeholders, aligning technical initiatives, and increasing operational efficiency. Led the implementation of ethical AI frameworks in advertising and enterprise ML applications, ensuring alignment with GDPR, CCPA, and Microsoft’s internal governance standards. Tools/Frameworks: Python, R, SQL, Kusto, Git, Databricks, PyTorch, Keras, TensorFlow, Scikit-Learn, Azure, Windows, CI/CD Nov 2021 - Oct 2022

Doctoral Computer Science Research Program

Selected to participate in a competitive, intensive, part-time academic research apprenticeship program at Google Research. Accomplishments:

Synthesized research with industry experts to uncover valuable information and new discoveries/methods. Authored literature reviews on risk management and AI governance frameworks to investigate their impact on AI tool acceptance. Conducted and validated rigorous applications of causal inference and structural equation modeling to evaluate generative AI transparency impacts in commercial applications.

Google Jan 2021 - May 2021

Director, Data Analytics

Oversaw the strategy, scoping, engineering, and integration of marketing science solutions, capturing >$150M in revenue in the first year, servicing Fortune 500 brands.

Accomplishments:

Scaled data analytics operations of a centralized team of 15 FTEs, doubling the client base and increasing team output by 150%. Led the strategic planning, budgeting, development, and execution of timely and quality customer insights that enabled efforts to improve and enhance the overall customer experience and ROI. Championed the enterprise data and AI solutions, innovating the production and implementation of proprietary company technology for LTV, propensity, media mix, and attribution. Tools/Frameworks: Python, R, SQL, Git, Google Cloud, AWS, Linux, Jupyter Notebooks, Tableau, Looker, Funnel, Google Analytics, Adobe Analytics, CI/CD.

Wpromote Nov 2020 - Nov 2021

University of the Cumberlands, School of Computer and Information Science Carmegie Mellon University, Heinz College III of Information Systems Management Quantic School of Information Technology

PhD in Information Technology, Specialization in Artificial Intelligence GPA: 4.0/4.0

Master’s in Entertainment Industry Management, Focus in Business Analytics, Information Systems Master’s in Business Administration (MBA), Concentration in Data and Decisions (Statistics) EDUCATION

Otterbein University

Bachelor’s of Arts (BA)

Operations Research Analyst

Operationalized Netflix TV and film production space sales analytics through rigorous application of statistical modeling and business process engineering.

Accomplishments:

Conducted groundbreaking research on ethical AI transparency, producing actionable frameworks now referenced in academic and commercial settings.

Authored literature reviews on risk management and AI governance frameworks to investigate their impact on AI tool acceptance. products.

Conducted and validated rigorous statistical tests (PLS-SEM) to investigate the association between proposed AI framework components and transparency.

Tools/Frameworks: Python, R, SQL, Excel, Salesforce Sunset Studios (Netflix) Dec 2017 - Dec 2018

Manager, Analytics and Operations

Oversaw operations research analytics for Toyota Motor Vehicles full-service digital marketing and advertising firm. Accomplishments:

Developed budget prediction models that enhanced planning accuracy and streamlined Toyota ad production timelines. Implemented AI literacy and data fluency initiatives across business units, increasing analytics adoption and strategic alignment. Applied NLP to ad taxonomy, reducing classification errors and increasing campaign clarity. Tools/Frameworks: Python, R, SQL, AWS, Linux, Jupyter Notebooks, Keras, TensorFlow, Scikit-Learn, Tableau, Google Analytics, Adobe Analytics, Salesforce.

Saatchi & Saatchi May 2020 - Nov 2020

Manager, Analytics and Data Science

Oversaw operations research analytics for Toyota Motor Vehicles full-service digital marketing and advertising firm. Accomplishments:

Developed budget prediction models that enhanced planning accuracy and streamlined Toyota ad production timelines. Designed and deployed scalable analytics frameworks that provided actionable insights into global sales and marketing operations, driving double-digit increases in cloud service adoption. Applied NLP to ad taxonomy, reducing classification errors and increasing campaign clarity. Tools/Frameworks: Python, SQL, AWS, Linux, Keras, TensorFlow, Scikit-Learn, Tableau, Google Analytics, Adobe Analytics, Salesforce. Quigley Simpson Dec 2018 - May 2020

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