Full Stack Data Scientist | Machine Learning Engineer | Solution Delivery Lead

Professional Summary

I am a dynamic engineering leader with 15+ years of experience driving innovation in software delivery and technology integration, adept at navigating both startup environments and large organizations across industries such as automotive, telecommunication, travel, and public services. My expertise spans the delivery of large-scale, microservices, and cloud-native solutions, with a focus on aligning technology with business objectives. Over the past two years, I have dedicated myself to advancing my expertise in Artificial Intelligence, completing rigorous training programs and excelling in courses focusing on Data Science, Machine/Deep Learning, LLMs, and MLOps. I bring an entrepreneurial mindset with zero-to-one experience, having scaled products from concept to production in startup environments. Tenacious and proactive, I take ownership and accountability, and I am seeking a challenge that will allow me to leverage my extensive IT experience combined with my growing skills in AI.

Professional Education

• Professional Certificate in Applied Data Science (Massachusetts Institute of Technology / April 2024 / 3 months training)
  Focus: EDA. Data Preprocessing. ML/DL Algorithms. Data Augmentation. Hyperparameter Tunning.
  Skills / Tools: Jupyter Notebook. Advanced using of Python libraries for data science and ML. TensorFlow. Keras. SciKit-learn.

• Data Science on Cloud (Great Learning / August 2024 / 3 months training)
  Focus: Implementing ML Solutions on AWS and Azure cloud services, MLOps, and end-to-end ML workflows.
  Skills / Tools: AWS IAM, CloudFormation, CodePipeline, Sagemaker Studio, S3, CLI, CloudWatch, Amplify, Sagemaker Pipelines, AWS Endpoints. Monitoring Data and Model Drift and retraining. Developing Data Science / Machine Learning / LLM solutions on AWS.

• Generative AI for Natural Language Processing (NLP) (Great Learning / September 2024 / 3 months training)
  Focus: Advanced Prompt Engineering. LLM Approach Evaluation. LangChain Agents. Developing Retrieval-Augmented Generation solutions.
  Skills / Tools: PyTorch, Hugging Face, OpenAI, LangChain, llama-cpp, GPU optimization, BLEU, ROUGE and BERTScore, Faiss, Chunking, Embeding, PEFT, QLoRA.