Data Scientist @ Mastercard | MSc, MLOps, Machine Learning, NLP, Artificial Intelligence | 3 X Microsoft Azure | 3X AWS

Certified AWS and Azure Machine Learning Engineer with 4+ years of experience in developing, deploying, and monitoring scalable NLP, Machine Learning, and Generative AI solutions. Proven ability to optimize processes, and implement impactful end-to-end AI/ML projects. Passionate about delivering data driven NLP, ML and AI solutions to complex business challenges.
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Note: Open to relocation | previous work authorization: PSW UK | require visa sponsorship for relocation 

As a data scientist, my expertise in Natural Language Processing (NLP) and proficiency in Python, coupled with practical knowledge of Generative AI and MLOps, positions me at the forefront of innovation in the field. With a focus on continuous learning and improvement through valuable certifications and projects, I am committed to deploying scalable solutions to create value for business.

### Technical Expertise & Project Highlights:

- 🐍 Programming Languages: Advanced proficiency in Python, Pyspark, and SQL for tackling diverse data challenges and developing scalable solutions.

- 🤖 Machine Learning: Expert in designing and implementing models with a specialization in hyperparameter tuning using Optuna and efficient model development with LightGBM.

- 🌟 Generative AI: Implemented projects utilizing OpenAI APIs, LangChain, LangSmith, and Google Gemini API, exploring natural language processing (NLP) and large language models (LLMs) to create innovative solutions.

- 🔍 Big Data Analysis: Proficient in Apache Pyspark on Azure Databricks, streamlining big data processing and transforming complex datasets into valuable insights.

- 📊 Data Visualization: Crafted compelling visuals with Power BI, Tableau, and Python libraries (Matplotlib, Seaborn, Folium), enabling clear communication of insights to stakeholders.

- 🚢 Model Deployment: Orchestrated end-to-end deployment using Python Flask, Docker, and Kubernetes, achieving seamless integration into production environments and optimizing operational efficiency.

- 🔄 Version Control: Efficiently managed collaborative projects using GitHub, ensuring streamlined development and consistent version tracking.

- 🛠️ Platforms and Tools: Expertise in Azure Databricks, Anaconda, Jupyter Notebook, Spyder IDE, PyCharm, and Visual Studio Code for comprehensive project development and execution.