Mukul Sankule
Senior Data Scientist
Bengaluru
Summary
Certified Professional Data Scientist with 8 years of industry experience. Specializes in AI Agents driven solutions, Gen AI development, Production Level AI models, and LLM development. Proficient in Data Exploration, Demand Forecasting, Statistical Inference, Predictive Analytics, A/B Testing, Time Series Analysis, AutoML, Cloud Analytics, and Big Data. Skilled in utilizing tools such as Pyspark, Databricks, AWS, Python, Azure, SQL, R & Excel. Domain expertise includes Retail, FMCG, CPG, Supply Chain, Insurance, Marketing, and Technology. Known for delivering on-time and accurate solutions by effectively understanding client requirements and applying Statistical/ML techniques and analytical tools. Actively contributes to organizational initiatives through internal training and up-skill programs as a technical trainer. Experienced interviewer across different levels. Worked with notable clients including Nike, HP, P&G, Warner Brothers, Microsoft, L'Oréal, Unilever, CVS, and WinGroups/Masan Consumer Holdings (Vietnamese).
Overview
8
8
years of professional experience
8
8
years of post-secondary education
5
5
Certifications
2
2
Languages
Work History
Senior Data Scientist
Skellam AI
Bangalore
08.2024 - Current
- Leading a team of data scientists, data engineers and business analysts where we are working with a luxury retail client in US to develop AI Agent solutions both in predictive space as well as descriptive enabling automated solution that democratizes various use cases in the GenAI and LLM Data Science spectrum
- Also acting as a ML engineer to productionize live models using Google Cloud Platform
Senior Data Scientist
Masan Group
08.2023 - 04.2024
- Worked as a founding member of the data science and analytics team working across multiple projects contributing to business driving analytical insights as well as AI driven inventory optimization solutions
- Currently my model is running across major Vietnamese regions such as Hanoi, Ho Chi Minh, DaNang where the daily order scheduling is done on the basis of a demand forecasting model running at a daily store-product level
- This solution has contributed to lowering of the DIO (Days in inventory) by around 30 days as well as increasing DR (Dispatch rate by ~15%)
Data Scientist
Accenture
06.2021 - 07.2023
- Promotional Demand Forecasting
- Developed complete ML pipeline in azure databricks using pyspark framework to automate the process of inventory management
- Automated forecast of 50mil skus-stores 8 weeks out in the future to help planners and demand managers make better decisions thus reducing $10mil in inv cost and increasing $20mil in terms of revenue
- Designed approach for determining and managing future stocks of new items and new stores without relying on the available history of demand
- Employed series of ML techniques such as Dynamic Time Warping, Clustering and Multivariate Time Series Forecasting methods to build a combined approach for forecasting
Data Scientist
Mate Labs
09.2020 - 05.2021
- Built Forecasting Models for various CPG clients to solve the issue of demand management, revenue growth & inventory optimization
- Supply chain inefficiencies were identified and key metrics were decided
- Forecasted results were validated across both short & long term helping to improve sales efficiency and reduce inventory costs by around 10%
Sr. Associate Data Scientist
Affine Analytics
11.2019 - 08.2020
- Built an SKU rationalization model to optimize Assortment for one of the largest Consumer goods company which helped in a 15% lift in average revenue per SKU
- A robust methodology was designed which includes Identification and calculation of Key Drivers, Product Profiling, Store Clustering, and Demand Transference model
- Product Profiling is done through decision tree modeling & Store Clustering using Partition Around Medoid (PAM) algorithm
- Demand Transference captured using a Log-Log Regression model
Data Scientist
Affine Analytics
06.2018 - 10.2019
- Built a Sales Forecasting model for one of the largest Information Technology companies to set the quota for partners using Ensemble Modeling techniques such as Bagging, Boosting & Stacking
- Incorporated supervised learning algorithms such as Random Forest, Xtratrees, and Gradient boosting to develop a final stacked model using Parallel Processing for faster multiprocessing
- Coordinated with multiple teams for integrated solutions in production
- Did Post-Campaign Analysis for one of the largest American Multinational Technology companies to review the Ultimate Effectiveness of the campaign versus the objectives
- Provided business insights and solutions to the key stakeholders to Improve the Success Rate of campaigns while Minimizing Cost, as well as Identified the Probable Players to be targeted in the market
- Monitored the campaign health over the period of analysis using Two-tailed hypothesis testing and improved the conversions by ~17%
MACHINE LEARNING INTERN
Epilen
05.2017 - 07.2017
- Investigated the use of an SVM-based classification model to establish a Prediction Model of medication adherence
- Employed the conventional Logistic Regression based classifier as the benchmark model that showed 65% accuracy
- Support Vector Machine used with kernels to improve upon the benchmark model showing 25% more accuracy with fewer variables
- Principal Component Analysis used to develop the SVM classifier by decreasing variables and increasing prediction accuracy
- Appreciated for excellent work conduct and structured approach; Awarded the Best Project among other intern projects
RESEARCH INTERN
Australian Centre for International Agricultural Research (ACIAR)
12.2016 - 01.2017
- Company Overview: Research sponsored by the Australian Center for International Agricultural Research (ACIAR) of the Government of Australia
- The project was based on West Bengal (India) and Bangladesh focusing on: 'Promoting Socially Inclusive and Sustainable Agricultural Intensification in West Bengal and Bangladesh'
- The research was conducted undertaking study of Tea sector in India (West Bengal and Assam) focusing on the improvement in livelihood, social inclusion and sustainability of the value chain models with special reference to the marginalized section including women
- Value chain modifications have been recommended, analyzing existing literature as well as on the basis of secondary data using appropriate statistical tools and techniques
- The findings have been submitted for publication in ACIARs website
- Designed a Value Chain Model supporting linkages between stakeholders that minimized production cost by more than 30%
- Identified social inclusiveness by exploratory analysis of income patterns across different horizons using R ggplot2 and lattice packages
- Recommended value chain modifications through extensive statistical research and suggested necessary policy interventions
- Research sponsored by the Australian Center for International Agricultural Research (ACIAR) of the Government of Australia
Education
5-Year Integrated Master (B.Sc. + M.Sc.) - Economics
Indian Institute of Technology, Kharagpur
01.2013 - 01.2018
All India Senior School Certificate Examination (AISSCE) - undefined
Chinmaya Vidyalaya
01.2010 - 01.2012
All India Secondary School Examination (AISSE) - undefined
Chinmaya Vidyalaya
01.2009 - 01.2010
Skills
Gen AI LLM
AI Agents
Big data analytics
Statistical modeling
Predictive modeling
Time series analysis
Forecasting
Google Cloud
Azure Databricks
SQL
Python
Pyspark
Websites
Certification
Introduction to Data Science in Python
Timeline
Senior Data Scientist
Skellam AI
08.2024 - Current
Senior Data Scientist
Masan Group
08.2023 - 04.2024
Data Scientist
Accenture
06.2021 - 07.2023
Data Scientist
Mate Labs
09.2020 - 05.2021
Sr. Associate Data Scientist
Affine Analytics
11.2019 - 08.2020
Data Scientist
Affine Analytics
06.2018 - 10.2019
MACHINE LEARNING INTERN
Epilen
05.2017 - 07.2017
RESEARCH INTERN
Australian Centre for International Agricultural Research (ACIAR)
12.2016 - 01.2017
5-Year Integrated Master (B.Sc. + M.Sc.) - Economics
Indian Institute of Technology, Kharagpur
01.2013 - 01.2018
All India Senior School Certificate Examination (AISSCE) - undefined
Chinmaya Vidyalaya
01.2010 - 01.2012
All India Secondary School Examination (AISSE) - undefined
Chinmaya Vidyalaya
01.2009 - 01.2010
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