Curriculum Vitae

💼 Honours and Awards

Northeastern University, Boston, MA (Jan 2021 - May 2023)

GPA: 3.9/4.0
Coursework: MLOps, Machine Learning, Deep Learning, Algorithms, Natural Language Processing, Probability and Statistics, Data Mining, Data Management for Analytics

Indian Institute of Information Technology (IIITS), India (Sept 2015 - May 2019)

Coursework: Data Structures, Algorithms, Database Management, Linear Algebra, Engineering Probability, Statistics for Data Science.

Tausight, Boston, MA (July 2023 - Present)

Engineered an NLP model for detecting Personal Identifiable Information (PII) in electronic health records. Achieved a state-ofthe-art efficacy of 94% F1-score by fine-tuning an LLM model using TensorFlow and TFX in an agile workflow.
Orchestrated MLOps best practices with Airflow, ELK, DVC, MLflow, etc. for experiment tracking, model management, and data versioning, ensuring a streamlined workflow.
Established and managed robust MLOps pipelines, integrating CI/CD practices, version control, automated testing, ensuring seamless deployment of models into production environments while reducing deployment time by 25%.

Tausight, Boston, MA (Jan 2022 - Aug 2022)

Conducted research and developed an unsupervised anomaly-detection model to identify malicious applications in healthcare systems, resulting in a reduction of false positives by 15%. Deployed it on customer end points through GCP and Airflow.
Built end-to-end data pipelines using Python and SQ to process multi-tera byte customer data utilizing BigQuery.
Employed a wide range of advanced statistical tests, including chi-squared, z-test, t-test and ANOVA which validated the model assumptions, fine-tuned alert thresholds, and reinforced the statistical significance of anomaly alerts.
Generated comprehensive analytic reports on unprotected health information (PHI) on customer endpoints using a diverse array of data analysis tools while ensuring compliance with data protection regulations.

Youngsoft Inc., India (Jan 2020 - Dec 2020)

Engineered NLP-powered AI chatbot assistants for healthcare products, reducing customer support costs by 30% and enhancing customer engagement by 46%.
Developed them in Python with Rasa (an open-source ML framework), REST APIs, and deployed on servers through SQL, GitHub/git, Docker, and AWS EC2 instances while integrating with social media (WhatsApp, Facebook, Telegram, etc.)
Collaborated with cross-functional teams, including data analysts, and stakeholders, to define project goals, requirements, and deliverables, ensuring alignment with business objectives.

Northeastern University, Boston, MA (Sept 2021 - May 2023)

Tutoring students in Python, NumPy, Pandas, and SciPy to program Machine Learning algorithms from scratch.
Mentoring students on Machine Learning concepts with one-on-one tutoring and regular out-of-class assistance, conducting code reviews, and evaluating assignments.

Programming: Python, R, SQL, C++
ML Frameworks: Scikit-learn, TensorFlow, Keras, HuggingFace, PyTorch
Data Science Libraries: Pandas, NumPy, Spacy, NLTK, Gensim, OpenCV, SciPy, Dask, Matplotlib, Seaborn, Plotly
ML Techniques: Hypothesis Testing, A/B Testing, Regression, Classification, Clustering, Decision Trees, Dimensionality Reduction, Neural Networks, CNN, RNN, LSTM, tf-idf, word2vec, Embeddings, Transformer, BERT, GPT, NER
MLOps: git/GitHub, Docker, MLflow, Airflow, Data Version Control (DVC), TFX, Kubernetes, ELK, Linux, GCP, AWS