Chithira Raj

 CHITHIRA RAJ Toronto, Ontario  Summary Data Scientist with 4 years of expertise in statistical analysis, machine learning, and data-driven decision making. Proven ability to transform complex datasets into strategic insights, informing key business decisions. Experience in predictive failure analytics, invoice process analytics, NLP, predictive modeling, quantitative analytics and interested in exploring the realms of LLM and Deep Learning. Strong analytical and problem-solving skills, coupled with experience working in an agile environment. Technical skills and Tools: Machine Learning, Data Science, Python - Pandas, NumPy, SciPy, scikit-learn, spacy, Keras, Seaborn, TensorFlow, Matplotlib, PostgreSQL, SQL server, Power BI, Tableau, Azure Machine Learning, Microsoft Excel, Office, PowerPoint, Git, Docker, Anaconda, Jupyter notebook, Oracle, Apache Spark, ETL, Cloud, Big data, Pyspark, Unix, Java, A/B Testing Algorithms: Regression, Classification, Natural Language Processing, Hierarchical Clustering, Time series forecasting, Boosting, Decision Trees, Deep Learning, CNN, Nearest Neighbor Search, Prophet, Sarima, Pattern Recognition, Computer Vision, Logistic & Linear Regression, SVM Experience Data Scientist | VMware by Broadcom, India 05/22 - 01/24 Led the development of unsupervised hierarchical clustering model to detect ESXi host failures. Implemented a VPT based nearest neighbor search algorithm to enhance host failure prediction accuracy by 80%. Developed anomaly detection models using K-Means and Isolation Forest, to identify abnormal log patterns. Preparing executive level dashboards and reports to communicate data insights, model performance and future strategies. Data Scientist | Accenture, India 12/21 - 05/22 Implemented a Gradient Boost regression model using Azure ML to enhance invoice processing of Microsoft’s financial transactions, achieving an accuracy rate of 85%, expediting invoice approvals and payments. Designed a real-time resource performance management tool using HWES time series forecast model with a 90% accuracy in predicting future productivity. Collaborated with stakeholders to understand business requirements, evaluated model performance, ran statistical tests, optimized parameters, and informed strategic decisions, boosting business performance. Junior Data Scientist | Accenture, India 03/20 - 12/21 Developed a XGBoost Classification model to predict the invoice payment outcomes, with 80% accuracy. Utilized NLP techniques to implement sentiment analysis and topic classification model on vendor communication data. Predicted support ticket inflow using time series algorithms, achieving 90% accuracy. Systems Engineer | Infosys, India 10/19 - 02/20 Proposed a face recognition platform for detecting emotions in autistic people, with an accuracy rate of 80%, learning and applying Convolutional Neural Network (CNN) and Haar Cascade Classifier techniques. Acquired proficiency in Data Structures, Java, Python, and SQL through dedicated training. Education ANd ACCOMplishments Bachelor of Technology in Computer Science Engineering: Federal Institute of Science and Technology, 06/2015 – 06/2019 Received Accenture Core Value Champion Award for developing an innovative predictive analytical tool. CERTIFICATIONS Deep learning with Keras and Tensorflow – Simplilearn Generative AI with Large Language Models - DeepLearning.AI Microsoft Azure ML for Data Scientists - Coursera