I am a scientist-turned-data scientist with a huge interest in finding innovative solutions to everyday problems. I've been using python and SQL to build my data science projects since 2020. A 6-month data science course at Le Wagon helped me to learn and implement industry best practices and skills. Almost a decade of experience as a scientist and more than 3 year's training in coding and machine learning has prepared me on this journey. I love to do team projects and also contribute to 'AI For good' projects, which have positive impact on society and environment. I am looking forward to build my career in sustainable, social and climate-responsible financial projects and risk managements with my ever expanding data science and statistics toolbox.
Things I've done in the past in addition to my regular work in building machine-lerarning models to tackle money-laundering with our client bank:
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π worked on NLP and recommendation system (cosine similarity, knn) with vectorizers, transformers and LLMs as well.
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π± worked in MLOps (MLflow for ML lifecycle management, GCP and AWS for storage, running models and deployment throug APIs etc.)
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worked in original reserach projects in molecular physics and published results in leading international journals. My science research background spans over 10 years and I have worked on complex (and cool) projects like femtosecond (i.e. 1/1000000000000000000 th of a second) stimulated Raman spectroscopy, laser induced fluorescence of ultra-cooled molecules at 3-4 K etc.
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Libraries and tools: Pandas, NumPy, SciPy, Scikit-Learn, TensorFlow, Matplotlib, Seaborn, Plotly, Spacy, LLMs, Pinecone.
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Methodologies: Statistical methods: Bootstrapping, Hypothesis testing; ML methods: Classification, Linear and multivariate regression, deep learning, tee based models, pipelines, Grid/random search CV.
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π― Iβm looking to learn more about financial risk management through ML and statistical/mathematical modelling, quant analytics projects.
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π€ Iβm looking for help with understanding in-depth the working and performance metrics, infrastructure building and front-end dev.
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π¬ Ask me about Spectroscopy, Data processing, Data visualization, ML
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π« How to reach me: Linkedin : https://www.linkedin.com/in/shreetamakarmakar/
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π Pronouns: she/her
π§° Toolbox