Technical Skills: Python, SQL, AWS, Snowflake, MATLAB, Machine Learning, Data Modelling, TensorFlow, NumPy, Pandas, Scikit-learn, Deep Learning, Neural Networks, Keras
MSc. Management | University of Birmingham | 2023-2024
- Key Modules: Digital and Business Analytics, Organisational Decision Making and Operations Management, Sustainable and Responsible Business Practices, Corporate Entrepreneurship and Innovation.
B. Tech in Information Science and Engineering | BMS College of Engineering | 2018-2022
- Key Modules: Machine Learning, Database Management Systems, Big Data Analytics, Data Structures, Artificial Intelligence, Cloud Computing, Statistics, and Discrete Mathematics.
- Grade obtained: 8.20 GPA
Co-Founder @ Cargo Link | New Delhi, India (June 2023 - July 2024)
- Designed scalable web architecture on AWS, further cutting operational costs and boosting deployment efficiency. Skills Utilized: AWS CodePipeline, AWS ECS, CloudFront, Docker/AWS Kubernetes.
- Developed ERP features (Route planner) using machine learning techniques like genetic algorithms and decision trees to reduce transportation costs by 20% and improve delivery times. Skills Utilized: Data Modelling, Statistical Analysis, Python, Pandas, NumPy.
- Led the business analytics function, utilizing Python and Tableau to create actionable data visualizations, directly contributing to a 5%-6% reduction in outsourcing costs by streamlining internal processes. Skills Utilized: Data Visualization, Business Intelligence (Tableau, Excel), Problem Solving, Strategic Planning.
- Automated customer service with a GPT-powered chatbot, reducing response times by days and improving attention to queries 3 times faster, enhancing customer and client satisfaction. Skills Utilized: TensorFlow, Keras, Natural Language Processing (NLP), Scikit-learn, AI Development (Hugging Face Transformers, GPT).
Data Scientist @ Actuartech | London, UK (June 2022 - June 2023)
- Developed automated KPIs using Python and Streamlit, managing the full project lifecycle from concept to deployment, reducing data handling time and reducing the frequency of necessary checks to only 20%. Skills Utilized: ETL/ELT, Data Pipelines, Business Intelligence (Power BI, Python, Streamlit).
- Enhanced life insurance framework using reinforcement learning, optimized model training processes to efficiently utilize AWS resources achieving a 50% reduction in runtime and ensuring IFRS 17 compliance. Skills Utilized: Machine Learning, Deep Learning Applications (TensorFlow, PyTorch), Cloud-AWS Kubernetes (EKS) and AWS SageMaker.
- Developed automated data integration processes using Lambda for ETL jobs and RDS for data management, along with APIs for data feeding, resulting in a savings of over 200 hours/month of team labor. Skills Utilized: Cloud (AWS Lambda, AWS RDS, GCP), Python, API Integration (Google APIs).
Developer Internship @ Actuartech | London, UK (December 2021 - June 2022)
- Developed and launched a SQL & R training course, using technical knowledge to create content and collaborating in marketing effort, making it the third most popular offering on the platform within 3 months. Skills Utilized: Programming (SQL, R), Salesforce, Team Collaboration.
Business Analyst | Internship @ Starlink Logistics Pvt Ltd | New Delhi, India (June 2020 - September 2020)
- Analyzed 5 years of data using advanced data analysis in Python and Excel, coupled with business intelligence insights from Tableau, leading to a 15% cut in resource use and improved decision making. Skills Utilized: Data Analysis (Python, Excel), Business Intelligence and Visualization (Tableau).
- Led the implementation of a new KPI system by collaborating with departments for data collection and using Tableau for analysis and dashboard creation, enhancing operational efficiency. Skills Utilized: Data Visualization, Project Management, Business Intelligence (Tableau, Excel), Cross-Team Collaboration.
Developed an objective strategy for discovering optimal EEG bands based on signal power spectra using Python. This data-driven approach led to better characterization of the underlying power spectrum by identifying bands that outperformed the more commonly used band boundaries by a factor of two. The proposed method provides a fully automated and flexible approach to capturing key signal components and possibly discovering new indices of brain activity.
Used MATLAB to train over 100 machine learning models which estimated particulate matter concentrations based on a suite of over 300 biometric variables. We found biometric variables can be used to accurately estimate particulate matter concentrations at ultra-fine spatial scales with high fidelity (r² = 0.91) and that smaller particles are better estimated than larger ones. Inferring environmental conditions solely from biometric measurements allows us to disentangle key interactions between the environment and the body.
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- Data Decision-Making and Problem-Solving by PWC, Achieved in: 2024
- Deep Learning Specialization by DeepLearning.AI, Achieved in: 2024
- Machine Learning Certification by Stanford University, Achieved in: 2023
- IBM Data Analyst Professional Certificate, Achieved in: 2022
- Python Developer by Google, Achieved in: 2020