Triumph Urias, an alumnus of the esteemed Covenant University, is a seasoned ML/AI Engineer with a proven track record in designing and implementing artificial intelligence systems in production environments for a myriad of use cases.
During the groundbreaking Google Machine Learning Bootcamp in Sub-Saharan Africa (August 2022 - December 2022), Triumph exhibited exceptional skill and expertise, earning him the prestigious TensorFlow Developer Certificate from Google's TensorFlow team, an accomplishment which serves as a testament to his skills in building and training ML models using the TensorFlow framework. He also possess skills in the field of Generative AI, leveraging modern technology like LangChain and OpenAI to build innovative solutions. Triumph has years of experience building with the Python programming language and is also able to transfer this skill to various other languages like JavaScript, TypeScript and others. He's skilled in Google Cloud Platform technologies as well as Docker, Git and GitHub for Operations workloads.
In December 2022, Triumph completed the McKinsey Forward Program after 6 months of study with the McKinsey Academy, during which time he honed practical skills for success in the future of work. These skills include applying the McKinsey approach to problem-solving, effective and influential communication, developing mindsets for resilience and adaptability, amongst others. Having shown diligence and commitment to the process, Triumph earned a badge of completion to commemorate this achievement.
Triumph is an innovative problem-solver, consistently tackling complex challenges to deliver impactful solutions. He thrives in collaborative environments, where he not only adds significant value but also leverages the strengths of his peers to continuously learn and solve intricate problems.
An AI copilot allowing users ask natural language questions and get answers about
SEC fillings or Stock Prices of their choice companies. Equipped with tools for Retrieval Augmented Generation and internet access to get real-time stock prices.
Built using LangChain🦜🔗 | OpenAI | Streamlit ⚡| Kay
Try it out!
Project Link.
An AI-powered chat interface for querying and chatting with PDF documents. Built using LangChain🦜🔗 | OpenAI | Pinecone | TypeScript | NextJS 13.
Project Link.
Identity Check is a Flask endpoint to verify the face on a live image versus the face on an identification document and the name provided
versus the name on the document using computer vision and OCR ML algorithms.
Built using OpenCV | DeepFace | VGG-Face | EasyOCR
Project Link.
A Python Program to deploy a containerized service on Cloud Run using Pulumi
Project Link.
Generate Passwords, OTPs, PINs, API keys and Token lists with various options for customization.
Project Link.
An end-to-end project building a deeplearning model that reads a comment and gives it relevant tags as regards its safety or toxicity.
Project Link.
Triumph brings tremendous dedication, analytical depth and clear communication to any team. He also brings a great work ethic alongside strong problem solving and collaborative skills. Triumph was able to deliver real impact during his time on my team and I wholeheartedly recommend him based on his significant contributions as a Data Scientist at Insight7.
Triumph joined the Insight7 team with much talent as well as curiosity. Over the period we worked together, I've watched him hone his skills as a developer and take on advice from more experienced folk to be a much better contributor to our team both technically and otherwise. He would be a very valuable addition to any team he joins.
Triumph is an excellent data scientist, full of energy and persistent, he's someone any organisation would be proud of having. He's excellent and innovative from my observation working with him directly.
Triumph is an incredible person with great work ethic. Working with him was absolutely beautiful and any team would be lucky to have him. He is very creative and a witty problem solver. Pays great attention to detail and gets things done impeccably.
