Rahul Kumar

Data Scientist

Bangalore Urban, Karnataka, India9 yrs 8 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in building pricing optimization models.
Proficient in end-to-end machine learning infrastructure.
Strong background in demand forecasting systems.

Stackforce AI infers this person is a Data Scientist specializing in Machine Learning applications across B2B and B2C sectors.

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Skills

Core Skills

Machine LearningData Analysis

Other Skills

AWSAdobe PhotoshopAirflowAzureCComputer VisionCustomer ServiceDemand ForecastingDockerHTMLKubernetesMarkdown OptimizationMicrosoft ExcelMicrosoft OfficeMicrosoft Word

About

I am a Data Scientist with broad experience in pricing optimization, demand forecasting, and end-to-end machine learning infrastructure. At Walmart Global Tech, I focus on building pricing elasticity models and markdown optimization frameworks that support strategic pricing decisions and drive business impact. I have also developed demand forecasting systems adopted by cross-functional teams for inventory planning and operations. Previously, I worked at MakeMyTrip on the Flights Pricing team, where I built reinforcement learning-based dynamic discounting models. At ZS Associates, I contributed to a wide range of projects, including fraud detection using unsupervised learning, guided selling systems for B2B sales, and computer vision applications like receipt detection. Across these roles, I have consistently worked on full ML pipelines—from data processing to model training, deployment, monitoring, and explainability. I am proficient in Python, SQL, PySpark, Airflow, FastAPI, MLflow, Docker, and Kubernetes, and have hands-on experience with cloud platforms like GCP, AWS, and Azure. My modeling expertise includes XGBoost, LightGBM, Prophet, DeepAR, N-BEATS, SHAP, and Autoencoders. I hold a dual degree from IIT Kharagpur and received a part-time research consultant offer from WorldQuant India after a national-level achievement in their training program.

Experience

9 yrs 8 mos

Total Experience

2 yrs 6 mos

Average Tenure

4 yrs 4 mos

Current Experience

Walmart global tech india

Data Scientist III, Sam's Club

Dec 2021 – Present · 4 yrs 4 mos · Bangalore Urban, Karnataka, India

Demand Forecasting
Markdown Optimization

Demand ForecastingMarkdown OptimizationMachine LearningData Analysis

Makemytrip

Senior Data Scientist I

May 2021 – Dec 2021 · 7 mos · Bangalore Urban, Karnataka, India

Flights Dynamic Discounting:-
Worked on Multi-Armed Bandits ( Thompson Sampling ) + Deep Learning model to predict discounts for the MakeMyTrip and Goibibo brand.
Developed and handled various data processing, data validation and model training automated pipeline using Airflow.
Created dashboards for monitoring the performance of model in redash ( coded in SQL )
Tools Used : Python, SQL, Airflow, git, Redis, AWS, Sagemaker, S3, Redshift, Athena, Grafana, Scalyr, Docker

PythonSQLAirflowAWSSagemakerDocker+2

Zs

Data Science Associate

Jul 2019 – May 2021 · 1 yr 10 mos · Gurgaon, India

Patient Event Prediction:-
Developed an ML-based model to predict a certain drug for COVID based on his/her prior medical history, comorbities, and in-hospital journey.
Copay/PAP Fraud detection:-
Developed and deployed anomaly detection engine to detect fraudulent pharmacies / prescribers using an unsupervised isolation forest model; Supplemented the model through SHAP explanation
Used Spark framework to create featurization pipeline; Implemented ML-based system to detect data-drift in inference pipeline
AI Guided Selling:-
Developed a multi-model ecosystem focused on enabling inside sales teams for B2B companies,
Includes model to determine churn/leakage, lifetime value, upsell/cross-sell/net new sell, for a customer
Developed the models through an end-to-end automated model generation pipeline (AutoFeaturization + AutoML) and supplemented through an explanation model framework generating explanations at the global, cluster, and local levels
Deployed the AIGS model system using Docker and Kubernetes; Developed an orchestrator framework containing poller,
processor and trigger-monitoring module for scheduling and managing different modules of the model system
Receipt Detection using Computer Vision:-
Developed an object detection model using Faster-RCNN to detect receipts in the image; Implemented Transfer-Learning on pre-trained COCO weights and achieved a MAP of 85 %
Anomaly Detection:-
Developed an unsupervised anomaly detection framework to detect anomalous cohorts in their sales (NRx and TRx)
Scored the cohorts based on scores from six different techniques and its overall volume contribution
Tools Used : Python, R, Pyspark, Azure, Docker, Kubernetes, Databricks

PythonRPysparkAzureDockerKubernetes+2

Cartesian consulting

Data Science Intern

May 2018 – Jul 2018 · 2 mos · Gurgaon, Haryana, India

Purpletalk

Intern -Data Scientist

May 2017 – Jul 2017 · 2 mos · Hyderabad Area, India

Worldquant llc

2 roles

Research Consultant (Part Time)

Aug 2016 – Oct 2019 · 3 yrs 2 mos · Work from home

Developed statistical arbritrage to create investment portfolios with high profit margin and low turnover and backtested these model in web based tool called Websim developed by WorldQuant

Summer Trainee

Jun 2016 – Jul 2016 · 1 mo · Work from home

Simulated around 4500 alphas and developed 355 submittable alphas(statistical arbritrage) to create investment portfolios with high profit margins and low turnover
Researched and Implemented Mean-Reversion, Technical and Fundamental Alphas
Backtested these alphas by running simulation on a web based tool called Websim developed by WorldQuant
Achieved gold level in Worldquant summer training program and awarded a position of Research Consultant

Indian institute of information technology, allahabad, india

Financial Analyst Intern

May 2016 – Jul 2016 · 2 mos · Allahabad Area, India

 Analyzed and performed Competitive Analysis of the company based on the defined metrics among leading steel company
 Studied financial reports and checked the financial key ratio of Tata Steel , did a five years trend analysis and also compared its performance with other leading steel manufacturers
 Suggested some measures to improve their performance.