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Click here or scroll down to respond to this candidateCandidate's Name
PHONE NUMBER AVAILABLE EMAIL AVAILABLE LinkedIn GithubEDUCATIONMaster of Science in data science CGPA: 3.Street Address Dec 2023 Seattle UniversityRelevant Courses: Statistical Machine Learning, Probability for DS, Data Visualization, Intro to Deep Learning, Bigdata, Numerical MethodsBachelor of Engineering in Electronics & Communication CGPA: 3.5 Apr Street Address Anna UniversitySKILLSProgramming: python, R, SAS, C# Machine Learning: Pytorch, Keras, Tensorflow, NumPy, Pandas, Matplotlib MLOps: Git, Spark, DBs: SQL,Hadoop NLP / LLMs: Hugging face, NLTK Cloud : AWS Visualization : Tableau, PowerBIPROFESSIONAL EXPERIENCESeattle University Seattle, WAData Analytics Oct 2023 Dec 2023 Conducted hypothesis testing to assess the impact of the employer engagement score on campus recruiter performance, resulting in a 20% increase. Automated reports with VBA, saving 12 hours/week for strategic engagement. Effectively communicated technical insights, leading to a 15% increase in engagement. Seattle University Seattle, WAResearch Assistant Jun 2022 Jan 2023 Collaborated with executives to analyze stellar cluster properties using Bayesian Statistics. Utilized Gaussian Kernel density for cluster type determination from photometric data. Published a detailed research report on the experimental design in the AAS Conference. Camp Korey. Seattle, WAData Scientist(Project Coursework) May 2022 Aug 2022 Collaborated to optimized donor management statistically for improved fundraising. Established an engagement score through complex queries and KPIs from Customer Perspective Utilized MySQL and PowerBI for data exploration, providing actionable insights. Developed predictive ANN models with an RMSE value of 1.93 for forecasting donor engagement scores. IBM Chennai, IndiaSenior Data Analyst Aug 2016 Apr 2021 Designed and implemented a tool using MySQL and Unix shell script for post-migration data verification, generating end-user reports. Streamlined data loading into a star schema using SSIS Mappings and Reusable Transformations for efficient processing. Created interactive Power BI reports and dashboards, facilitating data-centric decision-making for clients and internal stakeholders. Established a fail-safe batch processing pipeline using Spark RDDs and data frames for data extraction, transformation, and loading.RESEARCH PROJECTSAmazon Product Recommendation Using LLMs Utilized advanced alignment techniques, including Supervised Fine-Tuning and Reinforcement Learning with Human Feedback, in conjunction with Collaborative Filtering, to tailor and optimize individualized product recommendations on the Amazon platform. Demonstrated proficiency in implementing LLMs, specifically the T5 model, to enhance accuracy and relevance in the Product FunctionalityIdentifying the Bird Species by their Call Using CNN Implemented CNN algorithms for bird species prediction, achieving 96.7% accuracy with a simpler binary classification model (convolution layer: 32,64; dense layer: 32,1) in 26 sec. The multi-class model with required more layers (convolution: 32,64,128,256; dense: 512,256,12), achieving 71% accuracy in 8 minutes, balancing accuracy, and computing speed. Using Decision Tree to Predict Teenage Substance Abuse Factors Utilized feature selection and ensemble methods, including bagging, and boosting, to enhance model performance. Achieved a 91% accuracy rate for binary classification of analysis. Multi-class classification using random forest predicted consumption risk with 47% accuracy. Regression model with boosting accurately predicted marijuana usage frequency |
