Experienced Data Scientist adept in statistical analysis, machine learning techniques, data cleaning, preprocessing, and transformation of large datasets. Skilled in data visualization and proficient in deploying machine learning models on cloud platforms. Strong communicator with the ability to convey technical concepts to non-technical audiences. Committed to continuous learning and staying abreast of the latest advancements in data science.
Advance Certification in Artificial Intelligence and Machine Learning
IIITH, India
Glasgow, United Kingdom (July-August, 2022)
Introduced a novel method evaluating the feasibility of approximating the top 10 neural model retrieved documents in an information retrieval task, employing a discrete search space optimization feature selection algorithm on datasets from both sparse models (ColBERT, MonoT5, DuoT5) and dense models (ColBERT PRF and ANCE) to train the BM25 statistical model.
Glasgow, United Kingdom (February-March, 2022)
Built a Spark-based pipeline project to assess the feasibility of information retrieval from extensive datasets, incorporating a query and inverted index approach to ensure optimal performance and deliver valuable insights in the field of news analytics.
Glasgow, United Kingdom (October-November, 2021)
Conceived and executed a project focusing on NLP sentiment analysis, leveraging Pandas, NumPy, and robust data pre-processing, integrating spacy tokenization, and implementing an encoder and classification model with One Hot Vectorization for efficient feature representation.
Glasgow, United Kingdom (September-October, 2021)
Utilized time series analysis and data visualizations to showcase essential variables, including trip frequencies within specific time frames based on geographical locations, and conducted a detailed analysis of taxi pickups at ten-minute intervals from designated locations.