I am passionate about improving outcomes through technology, data, and data science. My experience in AI-ML ranges from ideation to implementation, ML-Ops, and generative AI. In my previous roles, I have led teams working on AI-ML algorithms that required both supervised and unsupervised machine learning. This includes recommendation engines, classification, optimization, regression, natural language processing, and complex ensemble models like Next Best action/customer/etc.
My work has involved working cross-functionally with business stakeholders, and product and engineering teams to ideate and prioritize data science projects across global organizations. I also have expertise in decision intelligence - which combines fields such as AI-ML, and behavioral sciences, to support improved decision-making.
While my experience spans analytics, statistical analysis, traditional machine learning, deep learning, and most recently using LLMs for various tasks, the choice of methodology depends on the context, complexity of the data, and available resources vs. being pre-determined.
I also taught an application-oriented course on Text Analytics & Natural Language Processing (NLP) at the Wharton School at UPenn. The course focused on real-world NLP applications, starting from foundational NLP concepts, through different types of statistical NLP models, to various deep learning architectures used in NLP, and finally to transformer-based language and multi-modal models. We also covered how large language models are being fine-tuned, risks & safeguards around LLMs, RAG + LLM-based agents, and future opportunities for innovation.
Last, but not least - when it comes to data, my knowledge is specific and contextual, and I am by no means an expert. This includes intermediate-level data modeling for SQL and no-SQL databases, and most types of cloud data storage.
Skills
(*some experience)
Programming Languages
Python, R, Dart, MATLAB, C++, SQL, html, Jinja, Javascript, Ruby*.
Frameworks
TensorFlow, PyTorch, Pandas, NumPy, Scikit-Learn, LangChain, Transformers, FHIR, Flask, SQLAlchemy, Drift, Kubernetes, Docker, Airflow, Git, Gitlab-CI/CD, Flutter, Nginx*, Jenkins*
Technical Skills
Cloud computing (AWS, Azure, GCP), agile methodologies, MLOps, Scrum certified