AI/ML/DS and Business professional with a passion for turning complex data into smart, creative decisions that drive impact across businesses, people, and systems. Guided by the values below, I see myself as both a builder and an operator. Not just a strategist or storyteller, but someone who ships meaningful solutions.

I’ve helped Fortune 500 brands transform commercial, media, and consumer data into growth strategies and scalable data products. I’m known for translating complexity into clarity, especially at the executive level. My work style is collaborative, grounded in a builder’s mindset, and backed by cross-functional experience across marketing, finance, and product teams.

I believe in the rigor of research, but even more in making that rigor accessible, actionable, and timely enough to create real change. This means knowing how to communicate effectively, assess risks, think critically, and follow through with execution that matters.

When I joined FCB New York (Interpublic Group) as Director of Marketing Science , the Strategic Analytics team was focused solely on supporting the FDA’s anti-vaping and anti-smoking efforts. Over the following year, I led the expansion of the team’s scope and influence, earning a promotion to Vice President and growing a dedicated analytics pod that became integral to a wide range of brand, media, and innovation work.

We evolved from a single-account support team into a strategic partner across multiple high-profile clients, including Pringles, Listerine, Aveeno, Intuit, Centrum, Marcus by Goldman Sachs, Blue Cross Blue Shield, Verizon Value Brands, Spotify B2B, Vanguard, and the Gates Foundation.

I led cross-functional data and product workstreams that elevated marketing science across the agency, from building creative attribution and influencer optimization models to pioneering GenAI pipelines for audience simulation and insight acceleration. This transformation positioned the team as a key contributor to new business, creative development, and strategic planning initiatives.

As Manager of Business Insights & Analytics at Reckitt, I supported the Hygiene portfolio (Lysol, Finish, AirWick + Household brands) during a period of significant market disruption and transformation. I led initiatives that enhanced both strategic decision-making and team capability.

My work included applying Bayesian marketing mix and multi-touch attribution models to uncover promotion misalignments and targeting inefficiencies, driving stronger return on media investment across brands like Lysol, Finish, and AirWick.

To replace fragmented testing practices, I introduced a scalable experimentation toolkit leveraging in-platform and geo-based testing, which was adopted by nine brand teams and embedded into Reckitt’s product launch workflows.

I also collaborated cross-functionally to analyze pandemic-related shifts in consumer behavior and partnered with external vendors to strengthen analytical infrastructure and upskill the broader marketing team.

At Essence I co-led the development of privacy-compliant measurement products that strengthened client confidence and protected millions in billings.

My work specialized in digital attribution, DSP algorithm optimization, and incrementality analysis (all within a rapidly evolving privacy landscape). This role combined deep technical analytics with strategic consulting for clients such as Google, NBCu, and T-Mobile.

I launched a global brand-lift program aligned with GDPR and CCPA standards, enabling insight generation in the absence of third-party tracking and powering strategic decisions for the Google Pixel brand.

I also integrated Google Ads Data Hub with internal APIs, resolving fragmented measurement workflows and enabling the launch of eight new insights features while improving operational efficiency.

Accenture was the foundation of my career, where I progressed from Analyst to Consultant within Accenture Interactive (now Accenture Song) during a pivotal period of the group's evolution into a global leader in marketing and advertising services.

I gained hands-on experience across Digital Product Management, Experience Management, and Applied Intelligence, supporting Fortune 500 clients such as Johnson & Johnson, Nestlé, Hewlett-Packard, Santander, and TransCelerate BioPharma.

My work spanned both strategy and execution, including unifying UX analytics with attribution analysis to uncover performance issues for CPG and B2B clients, leading to responsive optimizations that enhanced customer satisfaction across the client’s brands. This experience equipped me with a strong foundation in integrating technology, business strategy, and analytics to deliver measurable impact.

Internship: Hands on experience working on distribution center and workforce analytics. Developed CUSUM model to get ahead of labor inefficiencies at the distribution center level.

Internship: Hands on experience working on retailer recommender system solutions. Refined recommendation algorithms for a major retail brand in the US.

Master’s in Behavioral & Decision Sciences

• Grade: 4.0/4.0 (with advanced Quant placement and PhD coursework)

• Concentration: Advanced Quant Placement + Economics PhD coursework

• Activities/Awards: Excellence in Applied Research Award

• Thesis: Behavioral Economics insights for Inter-American Development Bank

• Relevant coursework: Modern Data Mining & Advanced Regression, Mathematical Financial Economics, AI and Human Behavior, Experimental Methods, Interventions for Policy & Organizations, Data Science & Quantitative Modeling, Judgement & Decision Making, Advanced Financial Frictions Macroeconomics, Advanced Advanced Empirical Microeconomics

Bachelor’s in Industrial & Systems Engineering

• Grade: High Honors: 3.4/4.0 Ovrl & 3.7/4.0 Major (with grad level courses)

• Concentration: Statistics & Business Analytics

• Activities/Awards: Executive member of the Society of Hispanic Professional Engineers (GT SHPE)

• Thesis: e-Comm failure predictive system for Macy’s

• Relevant coursework: Computing for Engineers, Stochastic Systems, Probability & Statistics, Information Technology, Finance & Investments, Game Theory, Quality Statistics, Simulation Analysis & Design, Linear & Discrete Mathematics, Business Forecasting, Database Systems, Computing for Data Analysis, Data & Visual Analytics, Engineering Economy, Computational Problem Solving, Engineering Optimization, Calculus I, Calculus II, Calculus III, Physics I, Physics II, Program Design for Engineers, Introduction to Computer Engineering, Digital System Design

• Designing & Building AI Products & Services (MITx, 2023)

• AI Associate (SFDC, 2023)

• Tableau Specialist (SFDC, 2023)

• Product, brand, and consumer analytics

• Growth experimentation

• Marketing-Mix & Multi-Touch attribution deployment

• Finance & risk modeling fundamentals

• Program Management, up-skilling, and mentorship

• Stakeholder & Cross-Functional Alignment

• SQL (adv joins, window functions)

• Python (pandas, PySpark, numpy, matplotlib, seaborn, plotly)

• Cloud warehouses: BigQuery, Snowflake <- capable of learning others quickly

• Airflow <- just familiar, not an expert

• Feature Engineering

• Data Quality

• Python (scikit-learn, XGBoost, LightGBM, CatBoost)

• Deep Learning (PyTorch; CNN/RNN/Transformers) <- medium proficiency. Looking for opportunities to utilize this more.

• NLP (spaCy, some BERT)

• Recommenders, clustering, anomaly detection

• Model Interpretability (SHAP, some LIME)

• A/B & multivariate design

• Bayesian Methods (PyMC)

• BSTS Causal Impact (tf-causalimpact)

• Diff-in-diff

• Propensity Scoring

• BI Suites (Tableau, PowerBI, Looker)

• Interactive Dashboards (Observable/D3, Plotly)

• VERY good during showtime: PowerPoint/Google Slides