Education Link to heading

Masters in Data Analytics
Northeastern University, Boston, MA
Expected Graduation: December 2024
GPA: 3.9/4.0

Bachelor of Science in Information Science
Dr Ambedkar Intitute of Technology, Bengaluru, Karnataka
Graduation: June 2018 GPA: 3.46/4.0

Skills Link to heading

  • Frameworks: Pandas, NumPy, TensorFlow, PyTorch, Scikit-learn, BeautifulSoup, Scrapy, Langchain
  • Architectures: RNN, LSTM, GRU, Seq2Seq, Transofrmers, Autoencoder, VAE, GAN, Diffusion models
  • Databases and Datawarehouse Tools: MySQL, PostgreSQL, MongoDB, Snowflake, Talend, ChromaDB, DataStax
  • Cloud and Visualization Tools: GCP, AWS, Tableau, Power BI
  • MLOps and CI/CD: Airflow, MLflow, TFX, DVC, Docker, Kubernetes, GitHub Actions
  • Programming Languages: Python, Java, C++, C#
  • Automation Tools: Automation Anywhere, Power Automate, UI Path, RulAI, VB Script
  • Project Management Tools: Jeera, Workzone, Monday.com

Projects Link to heading

Work Experience Link to heading

Data Analyst
FHI 360, Washington, DC
Jun 2023 – Nov 2023

  • Reduced patient dropout rates from 72% to 51% by identifying key parameters that corelated directly to patients at high risk of treatment interruptions and implemented Gradient Boosted Trees on them achieving an accuracy of 65%.
  • Deployed a Python RAG framework, allowing users to query in natural language and retrieve answers from relevant document embeddings stored in a vector database reducing time spent on searching documents for information.
  • Developed dashboards on market trends and competitors using Power Bi to enhance scope of studies for project viability ensuring cost-effective decisions achieved by transforming data from various public sources into a warehouse on Azure.
  • Engineered a Python framework to extract Congressional Budget Justification data, providing a strategic forecast of project outlook and funding allocations for upcoming fiscal years in specific regions and countries through dashboards.

Senior Automation Engineer
Acronotics, Bengaluru, India
Jul 2019 - Sep 2022

  • Cut recruitment time by 65% by developing a python framework to scrape candidate info from LinkedIn.
  • Reduced time for shortlisting by an additional 25%, using a Gaussian Process Regression model trained on partners historical data.
  • As the solution architect improved user experience by designing dashboards to monitor bot performance and augmented features like auto-ticket assignment, auto-rescheduling into RadiumAi, a product to maintain RPA process across platforms.
  • Reduced helpline wait time by 70% by building a chatbot that used few shot examples & document retrieval to solve queries.
  • Enhanced chatbots ability to retrieve relevant info by using a hybrid approach combining TF-IDF sparse embeddings and attention-based dense embeddings, achieving a 12x speed improvement and a 65% increase in accuracy.
  • Increased memory utilization and decreased training runtime through data and model parallelization techniques, enhancing the efficiency of machine learning workflows.
  • Reduced payment term from three days to one by implementing OCR to automate invoice processing, therby accelerating the payment cycle and improving supply chain efficiency.
  • Eliminated dependency on users and ensured consistency by automating data collection, manipulation and report generation.

Data Engineer
Tata Consultancy Services, Bengaluru, India
Jun 2018 - Jul 2019

  • Streamlined data flow for analysis by designing and deploying pipelines that ingest data from AWS S3 buckets into Snowflake and automate transformations through Streams and Tasks, resulting in consistent and efficient data processing.
  • Deployed scripts to automate data extraction, transformation, and visualization from over hundred data sources, ensuring real-time updates and enhancing data accessibility for upstream tasks.