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.

Virginia Tech

Graduate Teaching Assistant

iLink Digital

Generative AI Scientist

Fidelity Investments

* Engage in strategic Data Science (Natural Language Processing, Machine Learning and Computer Vision) to enhance processes within Asset Management 
* Research new tools and technology in Deep Learning and Natural Language Processing, conduct experiments and build highly optimized novel solutions to automate tedious manual processes 
* Identify potential new use cases and present research findings to non-technical and technical stakeholders, collaborate with cross-functional engineers to develop, deploy and document heavy models handling hundreds of GBs of unstructured data 
* Analyze financial reports to automate custom tagging of text data to speed up the development of dashboards and forecasting models. 
* Developed an interactive low code tool to create automated news summaries in real time with simple keyword searches using transformers and open source APIs to optimize news accessibility to employees across Fidelity.

Data Scientist 

Northeastern University

Python (NumPy, Pandas, Matplotlib, Seaborn), Machine Learning (Regression, Classification, Neural Networks)
* Mentored 300+ students from non-CS backgrounds in Python and Data Science for ‘Programming with Data’(DS2000)
* Held office hours, created, and graded assignments, managed practicum classes, reviewed project presentations.

Northeastern University Information Technology Services

Customer Experience Technician

• Established an ETL pipeline leveraging financial data with billions of records to map new financial assets with short history to top similar assets with long history. Contributed to a revenue of $30 million
• Performed OLAP using spark UDF and conducted EDA to analyze historical trends. Built a scalable large-scale distributed collaborative filtering-based model, tuned hyper-parameters to generate reliable expected returns of assets. 
• Conducted A/B tests to identify and retain important features, and to choose the best variant of the model among many. 
• Worked with cross-functional engineers and integrated the proxy logic with the asset simulation pipeline and deployed it to production. Configured the user API for users to customize and analyze their investment portfolio.
• Simulated conditional beta of assets by training and tuning an XGBoost regressor model on data with thousands of features using Map-Reduce. Speeded up execution by 15 times by reducing dimensionality with Autoencoders.
• Optimized the portfolio investment returns by building a factor simulation model to analyze the risk of hundreds of factors using Variational Autoencoders and Gaussian Mixture model. Automated the pipeline and saved 40h/month.

Data Scientist

• Analyzed large amounts of customer data and created dashboards to extract useful patterns and identify anomalies to improve customer experience and optimize data flow. 
• Provided on-campus as well as remote IT support to Northeastern community by troubleshooting and fixing computer hardware, software issues.
• Attended 1000+ customer calls (with a customer rating of 4.5) and resolved technical bugs with the help of remote sessions and by coordinating with Northeastern's IT experts and co-technicians.

Indian Institute of Technology, Hyderabad

•	Collected and cleaned streaming data from online sensors, cleaned and engineered required features for analysis. 
•	Optimized the design of a hybrid power generator by training and tuning an ANN and improved output by 29% 
•	Built dashboards via Tableau to analyze model parameters, performed A/B testing to quantify feature success.

Summer Research Fellow

Mangalore Chemicals and Fertilizers Limited

• Designed and tested an efficient parallel transformer architecture to reduce electrical power loss and minimize power transmission costs. Achieved a power saving of 5.3%
• Researched and proposed automated control systems for the power grid system to extend battery life . 
• Gleaned data from sensors and numerical arrays and analyzed circuit breaker faults using MATLAB and Python. Suggested improved design techniques to prevent catastrophic faults and saved equipment expenses.

Electrical Engineering Intern

Everything I share on this platform is my personal opinion and does not represent the organization that I work for. 

Data is the new oil! It is incredible to see how data is taking over the world of technology and is enabling making complex business decisions easier by each day. Data Science fascinates me because it is systematic, artistic, involves a diverse set of skills, and is ever-evolving. Data extracts meaning out of the mess and adds value to people's lives. 

In the journey of finding my true passion amidst innumerable possibilities, I have found that Data Science is what I want my career to be in. It feels right and makes me happy and proud of what I am doing. And so, after completing my bachelor's of engineering in Electrical and Electronics, I pursued and graduated with Master's in Data Science at Northeastern University, Boston. With extensive experience in working on Data Science projects across various domains, I have gained expertise in handling huge amounts of data, building and deploying data pipelines, and analyzing performance by creating domain-based metrics. 

I completed my Bachelor of Engineering in Electrical and Electronics Engineering at Sri Jayachamarajendra College of Engineering, India, where I was exposed to Machine Learning and Deep Learning techniques. I worked on several projects like designing and optimizing electrical network architectures using my newly attained skills in Data Science. I recently finished my Co-op as a Data Scientist at Fidelity Investments, where I worked with cross-functional engineers to build and deploy large-scale distributed ML models and pipelines to predict trends in financial stock data and maximize expected returns of stocks. 

I am proficient with Python and R. My skillset also includes Machine Learning (Regression, classification, clustering, dimensionality reduction), Deep Learning (ANN, RNN, CNN, Autoencoders, Transformers, PyTorch, and Tensorflow), Database techniques (MySQL, SQLite, RMySQL, RStudio, XPath), A/B Testing, Hypothesis Testing, Snowflake, Airflow, PySpark, AWS, and Data Visualization (ggplot2, Matplotlib, Seaborn, Tableau). I am still enthusiastically grabbing onto new frameworks and techniques to be a better Data Scientist. 

In my free time, I write poetry and stories, create new music, or read books, preferably about Philosophy, Psychology, Neuroscience, and deeper aspects of life's beautiful nuances.

Kavana Venkatesh

taplio

The Battle

Matthew Blasa

Kavana Venkatesh

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