1. Worked with clients directly to develop predictive models andSegementation models as per the business requirement in order totargeted marketing2. Developed intricate algorithms for internal liabibity check to identifydefaulters and help stakeholders in making proactive decisions3. Built Responsible AI algorithm( Bias and Fairness methodology) from scratch adhering to regulationson gender and ethinicity bias in US.4. Implemented two important workflows in the existing ML pipeline which assessed the quality of data input in the model and the output results. This resulted in reducing errors, data load and improved effectiveness of model scores usage across verticals.5. Modeled predictions with feature selection algorithms.6. Set up Databricks database on cloud servers to store client data for queryanalysis.

GitHub: https://github.com/rit24101. Worked on foundations of NLP such as TF-IDF, Word2Vec, and more involved state of the art algorithms such as BERT for text summarization and its variations2. Build supervised learning algorithms for classification and regressions such as KNN, Logistic Regression, SVM, Naïve Bayes, Decision Trees, Linear regression in various situations alongside learning foundations of ML such as CV, Outlier Detection, Feature Engineering, Imputation, Curse of Dimensionality, Bias-Variance tradeoff, Performance Metrics, basics of solving optimization problems using various forms of gradient descent such as SGD, Batch SGDEnsemble models such as Random Forest, XGBoost, Stacking various models, Cascading3. Recommender Systems using Collaborative Filtering, Content-Based Filtering, Matrix Factorization (SVD)4. Unsupervised Learning: various forms of Clustering such as K-means, K-means++, K-Medoids, etc., Hierarchical clustering Techniques, and Density-based clustering5. Deep Learning using Tensorflow and Keras: Basics of optimizers such as Adam, AdaGrad. NAG etc, in Deep Multi-layer perceptrons, optimizers and activation units in various situations, CNNs, LSTMs, Encoder-Decoder models, Attention Models, Transformers, BERT, GPT-1,2,3

Working as a Senior Analyst in Paytm Stores vertical. We work closely with Business Heads, Product Managers and Engineers to analyse shortcomings and areas of improvements. My KRA includes :• Building the tracking from ground up for GA substitute internal analytical tool Pulse which led to better reporting of various points across the platform.• Working on Big Data using Hive to provide necessary data for onboarding, merchant supply, demand and sales.• Working with the Product teams on Merchant Discovery, Catalog and Post-Order to perform elucidatory analysis and check for the performance of new product features.• Trained and managed a team of four Data Analysts to provide end to end solutions across the organisation.• Automated Weekly Business Review which is used to empower KRAs of different teams.• Automated dashboards on Sales, Demand and Supply• Scaled the CLM program via reporting and inferential analysis which led to 6% WoW growth in revenue. This program helps merchant to target their Users via PNs as they enter their Geolocation• Assisted in automating Machine Learning Algorithm that can tell the propensity of users buying and target them accordingly.

Worked as a part of the core Data Analytics & Solutions team which works closely with CXOs, Product Managers, Marketing, Sales and Data Engineers. As an Analyst, I have worked on the following data driven projects and empowered decision making across different verticals :• Engineered the whole process of product tracking with product and tech team to analyse the performance of the product using Google Analytics• Identified user groups for Churn, RBNT and Retention programs by cohorting them on the basis of their shopping behaviour, RFM analysis and interaction with the platform• Tracking and Reporting for an Instagram Story style Content design to track the performance, retention, shares, and time spent by customers from different demographics. Performed various hypothesis testing.• Generate an NLP model to redevelop offer titles and bucket them to improve and monetise merchandising on the platform.• Helped business and sales teams in laying out their plans by understanding their business needs and goals and accordingly analyse the data by segmentation and bucketing• Performed in depth retention analysis. Concluded that rating prompt increases retention. Improved M1/M2/M3 retention rates by 4.8 % adding roughly 10k returning customers every month• Rolled out convenience fees using A/B Testing which led to an additional 25 lakhs per month revenue• Undertaking Data oriented Cost optimisation efforts to reduce querying cost by 2L per month.• Created a dashboard which highlights any impending risks of Customer Fraud on the basis of their recency, frequency and monetary values.• Built and maintained master derived tables from intermediate base tables through scripting to make transaction and GA Discovery data more accessible to the organisation• Trained and managed a team of 2 Data Analyst and 3 Interns to provide end to end solutions throughout the organisation

Automated business reports using Python Scripts. Created Power BI dashboards for various use cases across different verticals of the organisation. Analysed data sets on excel and drove useful inferences.

Used excel for Data Cleaning and Modification, and consumed formatted data to derive inferences using Pivot Tables and Charts. Worked with numerous functions such as Vlookup, Index Match, SumIfs etc.