I’m Tirus Kimani Wagacha — a Data Scientist & Backend Software Engineer specializing in Generative AI, LLM-powered analytics, and scalable systems that turn complexity into clarity.
I’m a data scientist and software engineer passionate about building intelligent, data-driven systems that drive measurable business impact. I specialize in merging scalable backend engineering with generative AI, NLP, and analytics to automate insights and empower decision-makers.
Currently pursuing an M.S. in Data Analytics at Kansas State University (4.0 GPA), I bring experience from fintech, logistics, and insurance domains. My work centers on designing LLM-powered agents, self-serve analytics tools, and insight automation pipelines that simplify complexity and accelerate outcomes.
Ask about my work, projects, or how I build intelligent systems.
Combining analytics, engineering, and AI to build intelligent systems.
Data manipulation, ML pipelines, automation, and agent logic.
Complex queries, data modeling, and scalable storage (MongoDB/MySQL).
Power BI, Tableau, narrative-driven insights for decision-makers.
Predictive models, transfer learning, LangChain, GPT-4 integrations.
Real-world solutions combining data, AI, and systems engineering.
Explored government agricultural subsidy distribution across Kansas, Nebraska, and Oklahoma to surface inefficiencies and strategic positioning for livestock farmers using Tableau.
Investigated discount strategy effects on customer trust and engagement, balancing perceived value and ratings using Amazon sales data.
Transformed and visualized responses from 600–700 data professionals to surface trends around compensation, job satisfaction, and tooling preferences in the data industry.
Combined customer review sentiment with embedding similarity search (FAISS) to produce context-aware product recommendations.
Analyzed hotel reviews to help AfriDusky Tours & Travel Agency enter the Kenyan market with customer-centric insights on satisfaction, strengths, and improvement areas.
Explored IMDb scores through regression, classification, and clustering to uncover drivers of ratings and group movies by meaningful patterns.
Analyzed the determinants of "Office Star" selection using a binary logit model to understand decision drivers.
Used SQL to analyze pandemic metrics across countries—cases, deaths, death rates, and vaccination progress—to surface insights on global impact.
Identified preferred hotel design attributes and trade-offs using conjoint analysis to inform user-centered hospitality design decisions.
Explored demand and compensation trends in the data analytics job market, focusing on high-growth roles and skill salary alignment.
Whether you're interested in collaboration, roles, or just want to chat about intelligent systems — drop a message.
© Tirus Kimani Wagacha. All rights reserved.
Built with a blend of data, AI, and thoughtful engineering.