Highly skilled Data Scientist/Machine Learning Engineer with 9+ years of experience in industry and academia. Founder of Number Genius (numgenix) a career up-skilling platform for professionals and students. Extremely proficient in Python and various Machine Learning frameworks, with a proven track record of delivering successful projects and products. Expertise in deploying Machine Learning and AI solutions, improving model performance, and reducing operational costs. I've consistently demonstrated my ability to exceed project targets by leveraging multimodal techniques and innovative AI solutions. Adept at optimizing workflows, streamlining data pipelines, and building scalable architectures to tackle complex business challenges. Proven leader and mentor, with experience working with diverse teams and leadership styles. Passionate about uncovering insights and creating value from data. With a background in various domains, including Medical, Finance (Insurance, credit risk, bankruptcy), Real Estate and Market Research, I bring a diverse and adaptable perspective to any project. SKILLS: Programming Languages : Python, R, Matlab, Scala, Java, C, C++ Databases : MySQL, NoSQL, Postgresql, Dbeaver, Oracle, Mongodb, Neo4j, Firebase, Reddis Graphs : Knowledge Graph, GraphRAG, GAN, GCN, GNN, Cypher, SparkQL, Gremlin, GQL Visualization : Tableau, PowerBI, plotly, seaborn, matplotlib, Amazon Quicksight, Google Data Studio, Looker, Google Analytics Machine Learning & AI : Pytorch, Tensorflow, Keras, scikit-learn, Transformers, XGBoost, NLTK, Llama, LangChain, Hugging Face, RAG, Vertex AI, OpenAI Other Python Frameworks : FastAPI, Flask, Streamlit Parallel Processing : CUDA Big Data & Cloud : Apache Spark, AWS (Sagemaker, Lambda, EC2), GCP (Vertex AI, BigQuery), Snowflake, Databricks, Microsoft Azure, Heroku CI/CD & Management : Agile, Jenkins, GitLab, Docker, Kubernetes, Airflow, JIRA Scripting Languages : Perl, Javascript Operating System : Windows, Linux, Unix, MacOS