Ritika Mittal

Business Development Executive

Gurugram, Haryana, India2 yrs 3 mos experience

Most Likely To Switch

Key Highlights

Achieved 94.32% accuracy in demand forecasting.
Improved SKU availability from 30-40% to 80-90%.
Developed machine learning models for loan repayment prediction.

Stackforce AI infers this person is a Data Analyst with expertise in Retail and Fintech sectors.

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Skills

Core Skills

Data AnalysisMachine Learning

Other Skills

SQLPython (Programming Language)Business StrategyStatistical Data AnalysisOral CommunicationNoise ReductionPresentation SkillsAnacondaTopic ModelingCustomer DataTeamworkPyTorchAnalytical SkillsProduct AnalysisProblem Solving

About

As a versatile Data Analyst with a background in Electrical Engineering, I combine strong technical abilities with creative design skills and effective soft skills. I am proficient in Python, SQL, and TensorFlow, and have hands-on experience in data analysis. My design skills, honed through tools like Figma enable me to create intuitive and visually appealing solutions. I excel in communication, teamwork, and problem-solving, bringing a collaborative and innovative approach to every project. I am dedicated to continuous learning and consistently strive to enhance my technical expertise and creative capabilities.

Experience

2 yrs 3 mos

Total Experience

1 yr 1 mo

Average Tenure

1 yr 9 mos

Current Experience

Blinkit

Data Analyst

Sep 2024 – Present · 1 yr 8 mos · On-site

Owned Auto Replenishment System (ARS) for Frozen Category for 1,800+ dark stores across Warehouse-to-Darkstore and Direct-to-Store flows
Built Dual-Rep replenishment logic — improved frozen SKU availability from 30–40% to 80–90%; scaled to 40+ stores PAN-India, adding Rs. 25–30L/month in GMV
Developed Day-of-Week demand bump — improved weighted availability from 60–70% to 85–95% while maintaining 2–3 days DOI
Built LightGBM demand forecasting model — achieved 94.32% accuracy for New Year peak demand
Rebuilt CPD model with hour-level demand curves — improved forecast accuracy from ~70% to 88%
Implemented Funk-SVD collaborative filtering for darkstore–SKU propensity; used LightFM to solve cold-start for new SKUs
Cut ARS pipeline runtime by 57% (70 mins → 30 mins) through SQL optimization
Built analytics layer for Remote Monitoring System (RMS) — surfaced frozen-room health signals for Ops and Admin teams via Redash dashboards

SQLPython (Programming Language)Business StrategyStatistical Data AnalysisData AnalysisMachine Learning

Dmi finance private limited

ML Intern - Analytics

Jan 2023 – Jul 2023 · 6 mos · New Delhi · On-site

Worked on a project which includes use of python, machine learning and deep learning.
Build Machine learning models which are useful to solve customer loan repayment prediction problem.

Machine LearningOral CommunicationNoise ReductionPresentation SkillsAnacondaTopic Modeling+25