About

Jitendra Jangid is a Senior Data Scientist at Tokopedia, with over 4 years of professional experience in machine learning and data science. He is an expert in Natural Language Processing (NLP), Recommender Systems (RecSys), and Data Science Applications. Jitendra's main area of expertise includes data science, regression, support vector machine, naive Bayes, ensemble methods, clustering techniques, and deep neural networks. He is proficient in various libraries such as Scikit-learn, Numpy, Pandas, Matplotlib, Seaborn, Plotly, TensorFlow, Gensim, Pattern, NLTK, SpaCy, and StanfordCoreNLP. Jitendra is also skilled in programming languages such as Python, PySpark, R, SQL, C, and Matlab. He has experience working with technologies such as Amazon Sagemaker, Databricks, Google Cloud Platform, Airflow, MLflow, Visual Studio, Github/BitBucket, Jira, and Tableau. At Tokopedia, Jitendra is responsible for the Product Recommendation Engine, Candidate Generation, and Product Ranking. He has also worked on Next Category Prediction using BERT4REC and HyperRec. Prior to Tokopedia, Jitendra worked at Zomato as a Data Scientist, where he introduced a feature to simplify online food ordering and implemented a collaborative filtering based algorithm for user personalized dish recommendations. He also worked on customer analytics and segmentation, creating customer personas using clustering techniques. Jitendra has also worked as a Data Science Associate Consultant at ZS Associates, leading a team of 4 Junior Data Scientists in developing a robust information extraction and retrieval system to be used by various pharma clients. Jitendra holds a Bachelor’s Degree in Civil Engineering from IIT Kharagpur, where he graduated in 2018. He also completed his 12th grade from New Public Senior Secondary School, Kota (Rajasthan) and 10th grade from Tagore Senior Secondary School, Kuchaman City (Rajasthan). Jitendra's tech stack includes Data Scientist, Research Scientist, NLP, ML, Apache Airflow, Python, SQL, Naive Bayes, Neural Networks, Seaborn, Sagemaker, Databricks, BERT, Scikit, Deep Learning, TensorFlow, Pandas, Search, Text Classification, XGBoost, Spark, SVM, Web, RNN, and Flask. With relevant experience of