Akhil Bharadwaj Mateti

Data Scientist | Data Engineer | Helping automotive and GIS companies by streamlining scalable ETL data pipelines | Python | SQL | Azure | AWS | · Vishakhapatnam, Andhra Pradesh, India

With over eight years in technology, I approach challenges with a blend of curiosity and resourcefulness, always seeking insightful and pragmatic solutions. My ambition drives me to continuously expand my expertise in data and cloud technologies, ensuring accountability and effective outcomes in every project I undertake.

Experience

Tech Support Coordinator

The George Washington University - Information Technology · Jan 2025 – Aug 2026

Not yet confirmed

• • Resolved 500+ customer issues for students, staff and faculty members in university for network connectivity, software installations in 6 months with a 93% resolution service level met.
• • Created self-help knowledge article for university students to download and install software for attempting their exams.

Data Analytics and Machine Learning fellow trainee

ElevateMe · Nov 2024 – Oct 2025

Not yet confirmed

• • Implemented data preprocessing and data cleaning, including imputations and removal of missing values, for an Azure SQL database of size 8GB for technology and entertainment-based clients.
• •​ Designed a Tableau dashboard analysing top cancellation reasons for events and discovered 2 agents involved in a total of 72.41% of total cancellations for the client.
• •​ Incorporated Multi-Layer-Perceptron (MLP) model for time-series based revenue forecasting for a client and achieved an R2 score of 66.59% on the test set.

Research Assistant

The George Washington University Columbian College of Arts & Sciences · Aug 2024 – Dec 2024

Not yet confirmed

• • Automated creating training, validation, and test splits by merging 2GB+ geojson files with shapefiles for African cities, ensuring data validation and spatial auto-correlation for model training.
• •​ Engineered a scalable ETL-based data pipeline in Python to process and resample over 144 large GeoTIFF files, leveraging multi-threading to accelerate I/O-intensive operations and reduce data preparation time.
• •​ Automated the feature engineering process by developing a script to programmatically extract and format contextual data from the pipeline, delivering analysis-ready datasets for downstream machine learning models for Nairobi.
• • Used machine learning algorithms like Decision Tree to predict the degree of deprivation in the Nairobi region, with a prediction accuracy of 69.86% for slums, leading to academic research with a paper accepted at the JURSE conference.

Technical Support Assistant - II

The George Washington University · Aug 2023 – May 2024

Not yet confirmed

• • Provided in-person and remote support for university students, staff, faculty and alumni for account recovery, software support and network connectivity across campus.
• • Contributed actively to the walk-in support team that achieved 60% first meeting and 75% on-time total resolutions.

Data Science Researcher

Data Science for Sustainable Development · Jan 2024 – Apr 2024

Not yet confirmed

• •​ Extracted and analysed raw data from almost 1000 Facebook posts on Yellowknife wildfire using Bardeen and Apify, resulting in significant insights about people preferring community aid influencing decision-making around using government aid.
• •​ Leveraged Python and NLP techniques for topic modelling on wildfire-related discourse, generating insightful word clouds aiming to discern public sentiments with a majority of people having neutral opinions on government aid, and achieving a coherence score of 49%.
• •​ Submitted a detailed report to a professor, who shared it with the mayor of Yellowknife, along with key insights comparing 57% reliance on community aid versus 10% reliance on government aid.

Technical Support Assistant - I

The George Washington University · Nov 2022 – Jul 2023

Not yet confirmed

• • Supported team members in a team of 6 to create self-help and knowledge articles, enhancing user support resources.
• • Coordinated troubleshooting efforts across multiple teams for network connectivity issues in campus dormitories.
• • Improved response times for technical support requests, contributing to a more efficient service delivery.

Project Engineer

Wipro Limited · Jun 2019 – Jul 2022

Not yet confirmed

• • Developed and implemented an over-the-air (OTA) update mechanism for software-defined vehicles (SDV), leveraging PyQT library in Python and establishing seamless backend communication via DDS and REST-based APIs.
• • Mentored 3 team members for the OTA project and was part of the SDV team that won excellence awards for Q3 FY2021.
• • Streamlined software deployment processes, cutting memory footprint by 350MB, by utilizing Docker, Kubernetes (K3s), and AWS CI/CD pipelines to enhance efficiency and scalability.
• • Improved autonomous vehicle performance by developing a real-time road region identification system using the FCN-VGG model.
• Integrated TensorFlow, PyTorch, and C++ wrapper modules, achieving a 12fps frame rate on a 5,000+ image dataset and reducing processing time by 10% per image frame.

G

Intern

gnani.ai · May 2018 – May 2018

Not yet confirmed

• • Built an automated ELT-based data extraction pipeline using Python and Scrapy, successfully retrieving over 10GB of raw data from 20+ media sources, enhancing the efficiency of speech technology projects.
• • Optimized data storage and handling processes by leveraging Google Cloud Platform’s (GCP) Cloud Storage, ensuring reliable management of datasets up to 25GB and improving scalability for large-scale data operations

What drives their work

The Architect

They design and construct robust systems to solve complex problems.

Akhil's superpower

You excel at transforming complex, manual processes and raw data into structured, automated, and insightful solutions.

How Akhil works

You are well-suited for roles that require a blend of analytical depth, system design, and practical implementation within data-intensive environments.