A seasoned Data Scientist with 6+ years of industry experience, adept at utilizing cutting-edge GenAI and Large Language Models (LLM) technologies to pioneer innovation in NLP applications across a range of sectors such as staffing, telecom, supply chain, and retail.Vivek has hands-on experience in building production grade solution using Generative AI using Large Language Models (LLM). He has worked on Fine Tuning Language Models, PEFT (Parameter Efficient Fine Tuning), Reinforcement Learning with Human Feedback (RLHF), Evaluations, and Scalable Retrieval Augmented Generation (RAG) as well.I am a passionate problem solver who leverages a diverse scientific and professional background to create innovative and efficient solutions. I excel in high-volume environments, bringing strong analytical, communication, and organizational skills to the table. With extensive experience in complex problem-solving, I thrive in fast-paced and challenging roles, driven to foster collaboration among teams. I aspire to become a leader and an innovator in the field of NLP and AI.My ability to swiftly grasp and adapt to new technologies has been pivotal to my success, and I am passionate about staying current with the latest industry trends and advancements. If you seek a highly motivated, detail-oriented professional who can deliver results in any environment, let's connect.Technical Skills• Programming Skills: Java, Python, R• Python Libraries: Pandas, NumPy, Sklearn, Matplotlib, Seaborn, Spacy, Nltk• Scripting Languages: SQL/PL-SQL, Unix shell Scripting, NoSQL• Framework / Platform: Hadoop, TensorFlow, Keras, OpenCV, AWS, LLMs,Langchain• Database: MySQL, Teradata, MongoDB• Tools: Eclipse, TOAD/SQL Developer, Putty, CI/CD tools(git, Jira, Jenkings), WinScp, MLOps, TableauKey Highlights:•Experience with Fraud, Risk or Financial Crime preferred •Relevant work experience in data science, machine learning, and business analytics •Practical data science experience with any of Python, R, Scala, PySpark or other relevant coding language and data science technologies •Strong proficiency in database technologies eg. SQL, ETL, No-SQL, DW, and Big Data technologies •Knowledge of machine learning modelling techniques and how to fine-tune those models eg. Random Forest, XGBoost, Neural Networks, Transformers, Markov chains, etc •Understanding and implementing new state of art techniques in the field of machine learning as they emerge
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