Sales Analytics / Python

Analyzed five years of data spanning over 7,000 implementations and developed predictive models using multiple regression techniques to identify key drivers of churn in enterprise SaaS deployments. Insights informed proactive customer retention strategies and to reduce implementation risk.

Strategy & Planning / Presentation

Aligned the team charter with corporate strategy pillars, shaping the broader alliances strategy in a business where partners drive over 80% of sales. Clarified objectives, roles, and core activities to strengthen collaboration and accelerate execution across high-stakes sales and delivery environments.

Market Sizing / Python & Tableau

Architected a repeatable and scalable Total Addressable Market (TAM) analysis framework by integrating World Bank macroeconomic indicators, LSEG industry benchmarks, and company-specific data. The interactive model quantified expansion opportunities across user segments, enabling data-driven market and feature prioritization.

Operations / Presentation

Created an operational framework to manage application lifecycle stages, from launch to scale. Research included deep dive into adoption and diffusion of technology to improve cloud services expansion and proposed supporting data driven analysis.

Marketing Analytics / Python

Built an interactive Sankey diagram to visualize partner marketing lead flow and drop-off points throughout the sales funnel, helping uncover buying path distortions, optimize campaign-to-close conversion and validate lead attribution.

Sales Analytics / Tableau

Developed sales dashboards and data sources to track partner-driven performance across 300+ partners and 2,400 accounts. Dashboards highlighted wins by industry, use case, and feature adoption, segmented by partner-sourced vs. influenced deals. Analysis included whitespace analysis and supported targeted account planning by vertical and sales stage per partner.

Product / Python

Built a deep learning–based recommendation system in Python using RAG and OpenAI’s foundational models to deliver contextual product suggestions through a chatbot interface. Combined semantic search and vector embeddings to analyze unstructured user reviews and dynamically generate tailored recommendations, showcasing how genAI can enhance decision support and product discovery in B2C.

Customer Insight / Python

Designed a data model to monitor near real-time platform adoption by integrating cloud telemetry, user activity, and support signals. Enabled early adopter identification and user segmentation based on behavioral usage patterns to inform targeted engagement and product-led growth strategies.

Data Driven Decisions / Review Article

Authored a thought leadership piece for executive review exploring technology adoption through the lens of logistic growth and S-curve models. The analysis examined adoption patterns of new features and applications over time, offering strategic insights into platform maturity, market saturation, and the timing of partner enablement, segmentation, and investment decisions.

App Strategy / Presentation

Led application strategy enablement by developing, organizing, and distributing content across the LMS, sales and marketing collateral portal, and a standardized set of blueprints and playbooks. Enabled partner readiness and go-to-market execution for new planning applications by delivering role-based guidance that accelerated adoption of high-impact use cases aligned to customer value.

Data Driven Decisions / Python

Analyzed referral and admissions data for a non-profit organization to identify macro-level trends and micro-level decision patterns impacting program access and outreach. Generated insights that informed strategic planning, optimized intake processes, and supported data-driven conversations with stakeholders and funders.