Shwetank Rokade

About Shwetank Rokade

Experience of 4+ years as a Data Scientist, currently working as a Data Scientist responsible for forecasting call volumes in a bank call center and non-phone (back office) volumes for different LOB like Debit Card Fraud Claims, Card Lending Services and HR. I excel in data integration, analysis, and building predictive analytics: Machine Learning and time series predicting techniques with accurate model diagnostics and evaluation using performance metrics. I am equipped with creating a user-friendly Streamlit webapp and Tableau dashboards to showcase daily and monthly performance analysis and forecasting KPI reports. Equipped with a Master\'s in Information Systems from Northeastern University, I\'m driven by innovation and passionate about leveraging data to drive business decisionsSkills:Programming Languages: Python, SQLLibraries: Numpy, Pandas, Matplotlib, Seaborn, Plotly, NLTK, Scikit-Learn, Keras, TensorflowDatabases: Snowflake, MS SQL Server, MySQL, PostgreSQLData Integration and Analysis Tools: Alteryx, Talend, Adobe Analytics, SSIS(ETL)Big Data Technologies: Spark(Pyspark, SparkSQL), Hadoop (HDFS, MapReduce, YARN, Hive, Pig)Data Visualization and Reporting Tools: Tableau, Streamlit, Microsoft Excel(Pivot Tables, Lookups), PowerPointCloud: AWS (S3, Athena, QuickSight, Glue, RDS, RedShift, Sagemaker)Machine Learning Algorithms: Linear and Logistic Regression, Decision Tree, Random Forest, XGBoost, K-Nearest Neighbors, Naive Bayes, K-Means Clustering, Support Vector Machine (SVM), Gradient Boosting Decision tree(GBDT)Natural language processing (NLP): Non negative Matrix Factorization (NMF), Latent Dirichlet Allocation (LDA), Bag of Words, NMF, Term Frequency Inverse Document Frequency(tf-idf), Word2Vec, Glove vectorsDeep Learning: Artificial Neural Network(ANN), Convolutional Network(CNN), Recurrent Neural Network(RNN), Long Short Term Memory (LSTM)IDE: Visual Studio, Netbeans, Jupyter Notebook, PyCharmEmail: s••••••••@gmail.comContact number:+91••••••••45Looking for full-time opportunities in the field of Data Analytics and Data Scientist roles

Experience

1. Quants Analytics Associate

   JPMorganChase

   Oct 2025 — Present · Mumbai, IN

   Consumer & Community Bank – Workforce Planning (Volume Forecasting)Supporting call center and back-office volume forecasting for Debit Card Fraud Claims, Card Lending Services, and HR by partnering with Capacity Planning, Risk, Finance, and Marketing teams. Optimized Workforce Costs with Real-Time Analytics: Designed and implemented a real-time predictive analytics dashboard in Tableau, reducing hiring FTE costs by ~$8M yearly for 12 LOBs Reduced Customer Complaints via NLP Segmentation: Used NLP-based techniques for customer segmentation to identify customer complaints, thereby achieving a 30% decrease in complaints for multiple LOBs Enabled Accurate Staffing with Data-Driven EDA: Performed EDA by handling, plotting, and feature engineering to predict call volumes for the correct staffing of handling calls in a call center Boosted Forecast Precision with Enhanced ML Models: Enhanced Machine learning and time series models, improving call volume prediction accuracy by 7%, enhancing workforce planning Maintained High Forecast Accuracy Through Model Monitoring: Tracked model performance by using various evaluation metrics and diagnostics for improving errors and maintaining 90% forecast accuracy Saved Time with Automated ETL and Live Dashboards: Automated an ETL pipeline using Alteryx, created real-time dashboards for KPI-based call volume performance tracking, saving ~2 hours daily Python Automation for Forecasting Efficiency: Automated holiday forecast charts in Python, saving 250-300 hours/year by replacing manual analysis using historical volume benchmarks Interactive Streamlit Web Application Development: Built a Streamlit web app for call volume analysis and model performance comparison, providing stakeholders with performance insights Delivered Actionable Insights Through Cross-Team Collaboration: Collaborated with cross-functional teams and stakeholders to support ad hoc business requirements, ensuring data-driven insights

Education

• Northeastern University

  Master of Science - MS, Information Systems

  2019 — 2021

• University of Mumbai

  Bachelor of Engineering - BE, Computer Engineering

  2014 — 2018