🚀 Results-driven Data Science Analyst with 2+ years of experience leveraging AI/ML to solve complex business challenges. Expertise in NLP, fraud detection, and customer churn prevention. Skilled in developing and deploying machine learning models, from traditional algorithms to cutting-edge LLMs. Proficient in data analysis, feature engineering, and creating impactful visualizations. Experienced in MLOps practices, ensuring scalable and maintainable AI solutions. Passionate about driving innovation and delivering data-driven insights to optimize business processes and decision-making. 📚 At Syracuse University: At Syracuse University, I wear the dual hats of Data Scientist and Research Assistant. Here, I'm exploring the uncharted territories of ML reproducibility and big data. My technical proficiency is reflected in my use of a dynamic tech stack including Python, R, SQL, Pyspark, and Scala, enhanced by cloud platforms such as Azure ML Studio and AWS Sagemaker. Complementing my hands-on experience, my academic journey in Applied Data Science is marked by a strong foundation in NLP, database management, and deep learning, alongside esteemed certifications from Google TensorFlow, Microsoft Azure, and IBM. 🔍 Skills: 1. Programming Languages: Python, R, SQL, Pyspark, Scala 2. Certifications: Google Tensorflow Certified, Azure Certified Data Scientist, Azure Certified Data Engineer, IBM Data Science & AI 3. Frameworks: MLFlow, Flask, Django, DVC, GIT, GitOps, Kubernetes, Agile, TensorFlow, API, Apache Spark, Hadoop, Kubeflow, Seaborn, Matplotlib 4. Database Management/ETL: SQL, Mongo DB, Cassandra DB, NoSQL, MS SQL Server, Spark, Snowflake, SQL Database 5. Machine Learning: Regression, Random Forest, XGBoost, Bayesian inference, Decision Tres, Scikit-Learn , SVM, Clustering Analysis 6. Cloud: Azure ML Studio, AWS Sagemaker, Azure Databricks, Azure Devops, Synapse, Azure Machine Learning, Azure Data Factory,AWS Glue, AWS Redshift, AWS Codebuild, AWS Codepipeline, AWS Cloud Formation, AWS Athena, AWS Lambda, AWS StepFunctions, AWS Managed Kafka, AWS Devops, AWS Athena, AWS Glue, AWS Redshift, AWS S3, AWS SNS, AWS EKS 7. Software Tools: Github, Docker, MS Excel, MS PowerPoint, MS Word, JIRA, Tableau, Gitlab, Neo4j 8. NLP/LLMS/Gen AI : Bert, Transformers, GPT-3.4, GPT-4, Cloude, Lllama, RAG , Vector Database. 🎯 My Goal: I'm passionate about leveraging my machine learning and data analysis expertise to create business impact, and eager to join a team where innovation and data-driven solutions thrive.