Zaide Islas
@zaideislas
I build demand, customer value, and experimentation models for ecommerce and marketplace growth.
SpainWhat I'm looking for
At Walmart Ecommerce, I lead full-cycle Customer Lifetime Value and demand-model development, from research and feature design through deployment, retraining, and performance evaluation. My models support CRM, Marketing, Commercial teams, and Ecommerce leadership in acquisition, retention, pricing, and planning decisions.
I build Python and Scikit-learn forecasting models with under 8% MAPE, analyze large transactional and behavioral datasets in BigQuery, and turn commercial targets into actionable customer-acquisition plans. I also automate data-quality monitoring with Python and OpenAI and Claude APIs, removing hours of manual verification each week.
Previously at Kavak, I used gradient boosting, segmentation, clustering, and A/B testing to understand marketplace funnel drop-off, demand, conversion, and retention. I created real-time Tableau reporting and defended causal findings and trade-offs with non-technical stakeholders.
My foundation spans machine learning, statistics, experimentation, SQL, PySpark, and data storytelling. I enjoy translating ambiguous business questions into analytical initiatives that Product, Commercial, Finance, Marketing, and Operations teams can use.
Experience
Work history, roles, and key accomplishments
Leads full-cycle development of Customer Lifetime Value models and predictive demand models, analyzing large datasets with SQL and Python to guide commercial strategy. Communicates findings through Power BI dashboards and executive presentations.
Designed and maintained an end-to-end ML forecasting pipeline for sales, improving forecast accuracy and eliminating manual forecasting. Defined metric frameworks for self-service analytics.
Built funnel velocity models and designed A/B tests to measure causal impact of interventions, improving conversion and retention. Created real-time Tableau visualizations for leadership.
Analyzed inventory and lead-time data using SQL, Python, Power BI, and Excel to model supply-side inefficiencies. Delivered data-driven recommendations that reduced part acquisition lead time.
Delivered quantitative market analysis of the Latin American pharmaceutical industry, supporting data-driven supplier negotiations.
Education
Degrees, certifications, and relevant coursework
Tecnologico de Monterrey
Bachelor of Engineering, Data Science and Mathematics
2020 - 2024
Grade: 96.25/100
B.Eng. in Data Science and Mathematics with an advanced specialization in Artificial Intelligence. Quantitative curriculum covering probability and statistics, statistical inference, experimental design, regression and predictive modeling, optimization, stochastic processes, machine learning and deep learning.
Tech stack
Software and tools used professionally
Availability
Location
SpainAuthorized to work in
Job categories
Skills
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