Machine learning Engineer with experience in ETL, NLP-based data processing, forecasting, predictive modeling, and end-to-end ML pipelines. Experienced in Python, Elasticsearch, Azure, AWS, Docker, Airflow, and machine l…
Machine learning Engineer with experience in ETL, NLP-based data processing, forecasting, predictive modeling, and end-to-end ML pipelines. Experienced in Python, Elasticsearch, Azure, AWS, Docker, Airflow, and machine learning research across biomedical and automotive data.
I am working on my thesis at Bayer where I am creating a centralized data repository for biomedical annotated data. This involves implementing named entity recognition and comparing different domain models to improve accuracy. I am also contributing to the development of a question answering system for biomedical data using GPT-J.
<p>Implemented ETL on annotated biomedical data from different sources and parsing it to one unified format (Json).<br>
Integrated data into Elasticsearch enabling easy utilization for machine learning research.<br>
Developed and compared fine-tuning of domain models using Bert, with the goal of enhancing Named Entity Recognition on the integrated Elasticsearch data.<br>
Collaborated in Research to provide solutions for Questing Answering system encompassing Data Generation, finetuning using Large Language Models and Generative AI Techniques.</p>
<p>Processed and transformed real-time data in different formats using Python libraries.<br>
Handled imbalanced and missing data that yielded significant improvements in accuracy of models.<br>
Created an NLP-based data processing preparation pipeline leading to increased accuracy, better predictions, and valuable insights, enabling faster model iteration and deployment by 20%.<br>
Developed ML end-to end pipeline that clusters defects reported by customers in automotive components.<br>
Co-ordinated the development and implementation of forecasting and predictive model, which helped in identifying different patterns and relations that provided impactful business processes that led to growth and innovation.</p>
<p>Collaborated in Agile Scrum Workflow and collaborated with Cross-functional team, gathering Business Requirements, design/execution of Python scripts to automate data triggering resulting in a 50% reduction in manual effort.<br>
Implemented ELT process, of extracting the financial data from Relational database using (Postgres SQL) or API integration.<br>
Evaluated data and performance metrics using data analytics tools for data Visualization and monitoring which helped provide valuable, innovative solutions to the client.</p>
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