About Me.
Welcome to my Digital Portfolio! I’m Tejas Pawar, a data scientist and machine learning engineer with specialized expertise in building end-to-end, production-ready ML solutions across NLP, computer vision, and large language models (LLMs). My proficiency spans Python, R, SQL, and cloud platforms like AWS and Azure, enabling me to deploy scalable, robust systems that drive meaningful insights and strategic impact.
My experience covers the full machine learning lifecycle, from data ingestion and preprocessing to model training, deployment, and monitoring. I’ve developed advanced NLP applications for real-time communication analysis, implemented computer vision models for complex image processing tasks, and fine-tuned large language models using tools like TensorFlow, PyTorch, and Hugging Face Transformers. With MLOps practices, I streamline development cycles, automate workflows, and ensure continuous model improvement, optimizing systems for both performance and reliability in production environments.
Beyond core ML capabilities, I integrate data engineering and visualization tools like Apache Spark, Power BI, and Tableau to create seamless user experiences, turning complex data into actionable insights. My projects include everything from automating data pipelines and deploying large-scale models to integrating AI-driven solutions into end-user applications, ensuring data becomes a strategic asset.
Currently, I’m open to freelancing, contract, and full-time opportunities where my blend of data science and machine learning engineering skills can add significant value. If you’re looking to leverage NLP, computer vision, LLMs, or other AI-driven solutions to advance your organization, let’s connect and discuss how I can support your goals. Reach out today, and let’s transform your data into high-impact insights!
Education
2023-2025
Boston University
Master of Science; Applied Data Analytics - Concentration Machine Learning; GPA 3.77
Awards: Teaching and Research Fellow
Coursework: • Analysis of Algorithm • Data Analytics with R • Data Mining
• Web Mining and Graph Analytics • Foundations of Machine Learning
• Designing and Implementing a Data Warehouse • Health Informatics
• Advanced Machine Learning and Neural Networks • Data Science with Python
2019 - 2023
D Y Patil International University
B. Tech; Computer Science Engineering- Concentration Data Science; GPA 3.65
Awards: Research Fellowship 2021, Academic Excellence Award Year (2022 - 2023)
Coursework: • Introduction to Python • Applied Computational Mathematics 1
• Applied Computational Mathematics 2 • Basic Electronics • Digital Logic Design
• Introduction to Communication Systems • Data Structures • Database Management Systems • Design Thinking • Computer Organisation • Computer Networks
• Software Engineering and Project Management • Introduction to Intelligent Systems
• DSP Systems • Database Systems • System Software • Embedded System
• Technology Commercialisation and Management • System Security
• Fundamentals of AI/ML • Principles of Data Science & Engineering • Deep Neural Networks
• Quantum Computing • Big Data Analysis • Knowledge Discovery and Data Mining
• Data Visualisation • Advance Data Science • Human Physiology (Health Data Science)
• Supply Chain (Open Elective 1) • Introduction to Fintech (Open Elective 2)
Experience:
Jul 2022 - Sep 2023
Data Scientist
Gera Developments Pvt Ltd
• Faced manual effort in handling customer queries, so developed and deployed a real-time sentiment analysis model for emails using NLP and Hugging Face's BERT, achieving 85% accuracy and reducing CRM workload by 15%
• Identified fragmented customer data, so led the development of the 'Customer Happiness Meter', a centralized platform that unified customer data, improving customer engagement and marketing strategies by 35%
• Resolved complex data challenges by collaborating with cross-functional teams to implement machine learning models, MS SQL, and ETL pipelines, delivering insights and meeting product requirements ahead of schedule
• Devised interactive Power BI dashboards to communicate technical findings to non-technical stakeholders
• Conducted A/B tests in Python using experimental design to evaluate the conversion rates of marketing campaigns, leading to a selected marketing campaign generating an additional $1.3 million beyond the projected revenue
Oct 2021 - Feb 2022
Data Science & Research Intern
Winjit Technologies Pvt Ltd
• Addressed inconsistent data across datasets by preprocessing 100GB+ of data using Python, leading to a 15% improvement in model training time and a 10% increase in prediction accuracy
• Tackled inefficiencies in building ML models by optimizing AutoML and Explainable AI algorithms, reducing time complexity by 20% and automating 80% of manual processes enhancing overall system scalability
• Solved client issue tracking delays by developing an interactive Power BI dashboard, reducing support response time by 25% and enabling 30+ clients to monitor performance metrics and trends in real-time