Matthew Blasa

LinkedIn

Contractor

Aspire360

Lead Data Scientist (Consultant)

Data Scientist & ML Engineer Consultant 

The Home Depot

Senior Data Scientist

Brinks Home Security

Solutions Architect- Analytics Center of Excellence 

edison.ai

Ruffalo Noel Levitz

Senior Data Strategist

Data Strategist 

Carrefour

Lead Analytics Engineer

University of Southern California

Senior Data Analyst

J.P. Morgan Private Bank

Data Analyst

Bridging the gap between data scientists and the business.

Learn more: 
AI Product and Strategy Substack:  https://datalife360.substack.com/
Pragmatic Data Scientist: https://pragmaticdatascientist.substack.com/
Linkedin Learning: https://shorturl.at/hg0Bc

Strategy Consultant

Interested in a discovery session?
email: info@aspire360.ai or DM me for more information.

•Context-Aware QA Chatbot: slashing client data retrieval time by 60% using 
Python, Langchain, and IBM Granite 3.2 LLM, integrating Elasticsearch for 
precise, data-driven answers from Proprietary datasets.
•Enterprise Scalability: End-to-End delivery (development through deployment) of 
scalable Generative AI and LLM solutions, customized to client workflows, 
demonstrably enhancing system performance and operational agility.
•Engineered autonomous AI agents using CrewAI and Llama 3.3, achieving a 40% improvement in decision making accuracy and response timeliness. Architected an intelligent framework that empowered the agent to dynamically select the optimal tool RAG for contextual data, a math tool for calculations, or real-time web search based on the user’s query. This multi-tool capability enabled robust, multi-step reasoning, allowing the agent to overcome base LLM limitations and deliver highly accurate, context-aware solutions.

AI Engineer

Thomson Reuters

•Developed all AI-driven Solutions in AWS cloud(Bedrock).
•GenAI Chatbot Development: Built and deployed AWS cloud-native (SageMaker, 
Bedrock) chatbots using Python, Langchain, and OpenAI (GPT-4 Turbo/GPT-4o), 
enhancing customer NPS score from 8 to 9 via transformer architectures and 
Advanced RAG.
•Enterprise Advanced AI Solutions: Engineered custom prompt workflows and 
Weaviate vector DB integration for optimized query processing, improving 
response accuracy by 25%+ using company-specific data.
•Customer feedback Insight Extraction: Leveraged NLP (Nltk) and LLMs to 
identify actionable pain points from unstructured text, driving data-backed 
product decisions.Leveraging this cutting-edge techniques to unlock hidden 
patterns and trends

Data Scientist

Convertcart

•Driven a 2% increase in overall sales and revenue by developing predictive 
models for customer engagement.
•Acquired and integrated datasets from multiple sources, performing rigorous 
Data Preprocessing to ensure data quality and accuracy.
•Conducted comprehensive Exploratory Data Analysis (EDA), Statistical Analysis, 
and Data Visualization to uncover key insights into customer behavior.
•Applied advanced Feature Selection techniques and Regression Modeling to 
build accurate predictive models for customer engagement scores.
•Implemented Unsupervised Learning (Customer Segmentation) to identify 
distinct customer groups, enabling targeted engagement strategies and 
optimized resource allocation.

Analyttica Datalab Inc.

•Developed and Dockerized deployment of an NLP solution using Python (NLTK, 
scikit-learn, TensorFlow) to automatically prioritize support tickets, significantly 
enhancing operational efficiency through Natural Language Processing.
•Delivered multi-million dollar cost savings and reduced ticket resolution time 
by 100 hours by accurately classifying priority issues using custom-built MLP 
models, demonstrating strong Predictive Modeling capabilities.
•Engineered robust end-to-end ML pipelines involving Text Preprocessing, 
Feature Engineering (word2vec, TF-IDF), and handling Imbalanced Data for 
Machine Learning model development.
•Implemented, evaluated (Model Evaluation), and optimized diverse ML algorithms 
(Logistic Regression, Decision Trees, Random Forest, Gradient Boosting) via 
Hyperparameter Tuning using Python (NumPy, pandas, scikit-learn).
•Managed the full MLOps cycle: instituted monthly model retraining, conducted 
A/B Testing for performance validation, and ensured continuous model 
monitoring in production using Deep Learning (TensorFlow) techniques.
•Proficiently presented technical solutions and impact analysis to stakeholder, 
translating complex Machine Learning technquies and Intelligent automation 
into business value (Stakeholder Communication)

AI Engineer @ IBM | 4 Yrs Exp. in ML, DL, DS, NLP, GenAI & Agentic AI | Ex-Thomson Reuters | VIT Alumni

Senior AI Engineer at IBM with a 4-years of track record of developing and deploying high-impact AI solutions. I thrive at the intersection of Machine Learning, Deep Learning, NLP, and the forefront of Generative AI. My toolkit includes Python, TensorFlow, Keras, and an advanced command of the modern NLP/GenAI ecosystem: LLMs, LangChain, RAG, prompt engineering, sophisticated fine-tuning, and vector databases,Tools,Agents.My analytical prowess is powered by Python (NumPy, Pandas, Matplotlib/Seaborn/Plotly), SQL, and robust data management practices. I am deeply passionate about pushing the boundaries of AI through continuous learning and creating innovative solutions.

Achutha Subhash

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Matthew Blasa

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