Ani Chitransh | Bayesian Regressions:Comprehensive analysis of the models utilized in Clumped Isotope Thermometry

Ani Chitransh

Data Scientist/Analyst/ML Engineer proficient in data modeling, AI, NLP & Deep Learning.

Based in Tucson

About

●Data Scientist with over 5+ years of experience in predictive modeling, data integration, & analytical reporting, leveraging Python, R, SAS, & SQL along with data science tools like pandas, Scikit-Learn, and NumPy, facilitating Excel & Tableau in business operations and data-driven decision-making by 20%. ●Working experience with data warehousing & ETL pipelines using Hadoop, Hive, AWS RedShift, Spark, & Airflow, enhancing data extraction & manipulation efficiencies across cloud platforms including Azure, Google cloud up to 15%. ●Proficient in implementing machine learning, Gen AI & NLP techniques such as A/B testing, time series, regression models,& gradient boosting, improving predictive accuracy.

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Bayesian Regressions:Comprehensive analysis of the models utilized in Clumped Isotope Thermometry

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About this project

The project aims to contribute to the scientific understanding of carbonate clumped isotope thermometry by investigating and evaluating various regression models, so we can get an idea of the best robust model under different conditions (e.g. error scenario, number of observations).