Machine Learning Data Science

Leondra R. Gonzalez, MBA

Indianapolis, IN *******.*****@*****.*** www.linkedin.com/in/leondragonzalez https://www.github.com/leondrajames EXPERTISE

Data science leader with over 10 years’ experience in delivering enterprise data-driven strategy and subject matter expertise spanning AI / machine learning, AI governance / ethics, big data, NLP, quantitative research, consulting, and information science. More than 6 years of experience leading teams of up to 15 data scientists, analysts, and engineers to drive business outcomes within the areas of corporate strategy, information technology, enterprise business development, digital marketing, operations research, and media. AREAS OF EXPERTISE

Strategic Transformation AI Strategy Data Science Machine Learning & AI Consumer Products Product Management Business Transformation Natural Language Processing (NLP) Engineering Leadership Cloud Computing Data Governance Agile Frameworks Software Development Life Cycle (SDLC) Client Management Change Management Process Improvement Strategy Model Deployment & Monitoring TECHNICAL SKILLS

Python (TensorFlow, Keras, PyTorch, Scikit-Learn) R SQL Java Kusto Bash/Shell Docker Dask Airflow Spark Hive Hadoop Sqoop Azure (Blob, Data Factory, Fabric, ML Studio, Synapse, DevOps) AWS (SageMaker, EC2, S3) GCP (BigQuery, AutoML) Power BI Tableau Looker Shiny Databricks Hugging Face OpenAI PROFESSIONAL EXPERIENCE

MICROSOFT, Indianapolis, IN Oct 2022 to Present

Sr. Data & Applied Scientist, Cross Solution Areas GTM Designed, developed, and advised on privacy resilient analytical deliverables used for global, multi-billion-dollar enterprise cloud-architecture deals for Azure Data & AI services and Connected Field Service Operations & Strategy.

● Developed a clear vision for the development and implementation of data-driven strategies to improve high-priority enterprise engagements and go-to-market approaches, resulting in a 15% improvement in customer targeting.

● Developed the vision and strategy for Sustainability SaaS sales’ analytics, influencing and informing both technical and non technical staff development, risk management, and operational excellence.

● Implemented multiple novel and complex technical solutions, including NLP machine learning tasks such as semantic textual similarity and summarization using an LLM to capture seller feedback of customer engagement summaries, resulting in a 50% improvement in proactive customer engagement feedback efficiency.

● Created and fine-tuned a revenue attribution model to quantify global seller influence on won deals, using an LSTM model and sequential data of deal sales funnel, helping the business identify sellers who require additional resources.

Sr. Analytical Program Manager (Sr. Technical Program Manager) Nov 2021 to Oct 2022 Managed offshore engineering and analytics team in the development of Bing and MSAN business performance reporting, KPIs, and predictive modeling.

● Oversaw a team of 15 data scientists and developers across project execution to build and deploy enterprise machine learning models, data pipelines, and accessability that improved the relevance and accuracy of search results, contributing to a 5% demand increase across 4 verticals.

● As technical lead, bridged the gap between analytics and company partners sales enablement initiatives by leveraging NLP, time series analysis, and deep learning methods.

● Broadly set the vision as the technical scientific advisor for Microsoft Advertising Sales Enablement by developing transformational programs and risk management processes, community culture, streamlining best practices, and protocol documentation.

● Ensured all data practices comply with ethical guidelines and regulatory standards while adhering to an agile software development lifecycle and CI/CD product roadmap for search keyword vertical classification model using the LLM, BERT.

GOOGLE, Los Angeles, CA Jan 2021 to May 2021

Part-time academic research apprenticeship program through Google Research, contributing to AI research. PhD Computer Science Research Program (CSRMP)

● Conducted research and wrote literature reviews on industry best practices for AI governance within LLMs and transformers (encoders, and decoders), including model validation, transparency and auditing.

● Collaborated with interdisciplinary teams of researchers to discuss developments and real-world applications of neural networks to address problems in healthcare, aviation, operations and marketing. WPROMOTE, El Segundo, CA Nov 2020 – Nov 2021

Reported to the VP of Digital Intelligence and Chief Technology Officer to design, implement, integrate, and deliver privacy-resilient marketing AI solutions, servicing Fortune 500 brands. Director, Data Analytics, Digital Intelligence

● Lead and mentored the interdisciplinary, central Data Analytics team of 15 data scientists, engineers and BI engineers to deliver customized, enterprise analytic solutions to Fortune 500 clients while overseeing project progress, budgets, and execution, resulting in a 150% increase in clients.

● Engaged with top customers’ consumer products and retail data and AI strategy, leading to the innovative production and implementation of proprietary company technology for LTV, propensity, media mix, and attribution.

● Conducted research in deep learning (LSTMs / RNNs), causal inference, game theory (ie: Shapley values), Bayesian structural time series analysis (BSTS), ensemble method forecasting and optimization for various marketing science applications including propensity modeling (RNN), predictive customer lifetime value analysis, media mix modeling and attribution.

● Presented findings and technical detail to key stakeholders to empower customers to capitalize on AI informed competitive advantages.

UNIVERSITY OF THE CUMBERLANDS, Williamsburg, KY (Remote) Dec 2019 – Dec 2023 Conducted research on information governance within generative AI and LLM applications in commercial settings. Doctoral Researcher, School of Computer and Information Sciences

● Led, developed, and executed quantitative, qualitative and mixed methods research on ethical commercial applications of generative AI, LLMs, and information governance frameworks from the perspective of underrepresented groups’ perspectives.

● Authored literature reviews on existing risk management information governance frameworks to investigate their potential in generative AI products.

● Developed a quantitative framework for identifying commercial AI footprints and opportunities for risk mitigation.

● Conducted a variety of statistical tests and modeling to investigate and validate the association between proposed AI framework components and public trust. SAATCHI & SAATCHI, Los Angeles, CA Dec 2018 – May 2020 A full-service digital marketing and advertising firm servicing Toyota Motor Vehicles. Manager, Analytics and Operations

● Guided corporate strategic objectives, including operational modeling excellence and planning by introducing business process ML models and kNN to provide annual advertising production and media budget predictions.

● Produced a supervised ML model to automate agency budget estimations, resulting in a more efficient and accurate delivery of financial reporting and expectations to the client (Toyota).

● Provided technical leadership and advised executive stakeholders on model results while addressing model drift by recommending retraining and validating procedures.

● Leveraged NLP and text mining techniques such as fuzzy matching and semantic similarity modeling to clean and categorize ambiguous terms, acronyms and misspellings of ad campaign taxonomy. QUIGLEY SIMPSON, Los Angeles, CA May 2020 – Nov 2020 A full-service digital marketing and advertising firm servicing P&G, First Aid Beauty, Dollar Shave Club, and more. Manager, Analytics and Data Science

● Championed the technical direction of client development and implementation of AI/ML models to create new data sets, simulate user behavior, and predict future trends for First Aid Beauty and Dollar Shave Club customers.

● Oversaw the creation and utilization of embeddings in machine learning models to capture the semantics of data, improve model performance, and provide more accurate insights.

● Developed and executed a data and analytics strategy that aligns with the company’s goals, including data collection, analysis, modeling, and interpretation.

● Collaborated with cross-functional teams to understand their business needs and identify opportunities for data-driven solutions.

HUDSON PACIFIC PROPERTIES, SUNSET STUDIOS (NETFLIX), Los Angeles, CA Dec 2017 – Dec 2018 A real estate investment trust (REIT) and management firm, overseeing the operations and sales of Netflix studios. Operations Research Analyst

● Defined bd infomed studio operations research projects strategy and introduced the application of GNNs

(graph neural network) using studio telecommunication utilization data to understand customer studio network usage, aiding in the development of a more equitable, consistent sales and pricing strategy for telecommunication services.

● Diligently performed exploratory data analysis (EDA), predictive modeling, and model deployment to incorporate the latest developments and emerging technologies in AI, machine learning, and data science. INTELLIGENT COMPUTER CONCEPTS (20TH CENTURY FOX), Los Angeles, CA Sep 2016 – Dec 2017 Manager, Supply Chain Analytics (Procurement)

● Led the procurement analytics team, overseeing over 2 million raw materials SKUs to provide data-driven insights for strategic decision-making.

● Developed and implemented data visualization tools to effectively communicate procurement performance metrics (KPIs) to stakeholders.

● Collaborated with cross-functional teams to optimize procurement processes and reduce costs for multiple promotions.

Data Analyst, Data Administration Nov 2015 – Sep 2016

● Managed and maintained the integrity of data within the DVD and BluRay department and utilized data visualization tools to present complex data in an understandable manner.

● Established goals and measurements to deliver tangible value to film/TV distribution promotions with partners.

● Performed statistical analysis to support business decisions and improve operational efficiency.

● Ensured data compliance and security by implementing best practices in data administration. PUBLICATIONS

Gonzalez, Leondra and Stubberfield, Aaren (2024). Cracking the Data Science Interview. Packt Publishing. Gonzalez, Leondra (2021). Walk First, Then Run: Why Data Governance Best Practices Are Essential to Advanced Modeling. Retrieved from: https://www.wpromote.com/blog/analytics/data-governance-best-practices EDUCATION

University of the Cumberlands, School of Computer and Information Sciences Doctor of Philosophy (Ph.D.), Information Technology, Specialization in Artificial Intelligence, Williamsburg, KY (In Progress)

GPA: 4.0/4.0

Quantic School of Business and Technology

Master’s in Business Administration (MBA), Concentration in Data and Decisions (Statistics), Washington, DC Carnegie Mellon University, Heinz College of Information Systems Management Masters in Entertainment Industry Management (MEIM), Focus in Business Analytics, Pittsburgh, PA Otterbein University

Bachelor of Arts, General Studies (Music, Business, and Management), Columbus, OH

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