Feb 2025 – May 2025 · 3 mos · Gurugram, Haryana, India · On-site

• Worked in Applied Intelligence Team of Accenture S&C.

Feb 2023 – Jan 2025 · 1 yr 11 mos · Mumbai, Maharashtra, India · On-site

• Leading end-to-end data science projects within GCPL's Indonesian geography. Awarded “Best Innovator” for building Machine learning based products at GCPL.
• Tech stack:- : Python, PySpark, MySQL, Azure Databricks, MLflow, Github, Machine Learning and Deep Learning
• 1. Forecasting Models:
• > Engineered end-to-end demand forecasting and outlet sales target forecasting models for GCPL’s
• Indonesian business, significantly influencing production planning, sales targets, and incentives.
• > This initiative impacted ~45% of GCPL’s total revenue.
• 2. Enhanced Forecasting Accuracy:
• > Achieved a ~10% increase in accuracy for non-promoted SKUs and a ~5% improvement for
• promoted SKUs, outperforming traditional consensus method.
• > Increased hit rate by ~20% and accuracy by ~4% for outlet sales target forecasting.
• 3. Automated Forecasting Pipeline:
• > Automated the pipeline to produce the forecast numbers, reducing the generation time from weeks
• to just 2 days for demand forecasting and by ~1 month for outlet sales target.
• 4. Recommendation System:
• > Building recommendation system to aid salesman to sell best potential skus per outlet to increase
• active outlets and revenue for ~2lakh outlets across Indonesia. Currently in the development phase.

Apr 2022 – Jan 2023 · 9 mos · Lucknow, Uttar Pradesh, India

• Tech stack: Python, SQL
• 1. Stock News Sentiment Analysis System
• > Designed and implemented a comprehensive financial sentiment analysis engine for a UAE-based
• brokerage firm, enabling real-time, data-driven insights into market sentiment through the
• analysis of news headlines and articles.
• > Leveraged Natural Language Processing (NLP) techniques, including tokenization, named entity
• recognition (NER), and sentiment classification, combined with machine learning models such as
• LSTM and BERT for accurate polarity detection in financial news content.
• > Developed algorithms to analyze sentiment trends in news articles related to publicly traded
• companies, providing actionable investment recommendations based on sentiment signals and
• historical stock performance.

Jul 2020 – Jul 2021 · 1 yr

• > Created a new machine learning model for prediction of B-cell conformational Epitopes.
• > Created new non-redundant training and testing datasets from scratch of antigen-antibody complexes collected from various databases.
• > Did extensive featture engineering to create ~12,000 features that collectively try to answer the complexity of epitope and non-epitope’s nature.
• > Explored various classical Machine learning models ( Tree based [like AdaBoost and XGBoost] ) and ensemble based classifers for best classification of epitopes from non epitopes.
• > Presented the findings in Indo-US workshop on “Application of Data Science in Biological Systems”, I.I.T Kharagpur.

May 2017 – Jun 2017 · 1 mo · Agartala, Tripura, India

• Significant achievements and Outcomes:-
• > Implemented different bioinformatics algorithms and techniques in MATLAB such
• as Needleman- Wunsch algorithm, BLOSUM matrix, and bioinformatics toolbox.
• Supervisors: Dr Sreerup Banerjee (Associate Prof., Department of Mechanical Engineering, Haldia
• Institute of Technology, West Bengal),
• Dr Tridip Kumar Bhowmick (Assistant Prof. Bioengineering Department),
• Dr Muthusivaramapandian M (Assistant Prof. Bioengineering Department),
• Dr Deeplina Das (Assistant Prof. Bioengineering Department).