Saket Nandan

Product Manager

Bengaluru, Karnataka, India4 yrs 11 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in machine learning and data science.
Led successful pricing optimization initiatives.
Developed automated data pipelines for efficiency.

Stackforce AI infers this person is a Data Science and Machine Learning expert in the E-commerce and Retail sectors.

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Skills

Core Skills

Data AnalyticsAmazon Web Services (aws)Machine LearningData ScienceData Analysis

Other Skills

AWS cradleAWS LambdaAWS GlueAWS S3Amazon RedshiftPySparksparkSQLPython (Programming Language)quucksightAmazon QuickSightAzure DatabricksDatabasesSQLBusiness AnalyticsMachine Learning Algorithms

About

---> Enthusiastic machine learning and data science expert ---> Impeccable knowledge for Algorithms, Data structures, Artificial Intelligence, Machine Learning, Deep Learning, Artificial Neural Network, Convolutional Neural Network, Recurrent Neural Network, ---> Statistics: Scaling, Transformation, Normalization, Descriptive, Inferential, Normal Distribution, Standard Normal Distribution , Binomial Distribution, Standard error, Hypothesis Testing, Z-score Distribution, T-Distribution, Chi-square distribution, Autocorrelation Function(ACF), Partial Autocorrelation Function(PACF) ---> Hypothesis Testing ----> Machine Learning Feature Engineer, Feature Selection, Regression(Linear, lasso, Ridge, Bagging, Boosting) Decision Tree , Logistic Regression, Random Forrest, SVM, KNN, Clustering, Time Series and Forecasting(Holt winters, ARIMA, SARIMA) Neural Network (RNN, LSTM, ANN) ---> Python : Pandas, Numpy, Matplotlib, Scipy, Sklearn, Seaborn ---> Business Inteligence tool expert:- google Data studio, Quick sight, Power BI, Tableau ---> Databases - MySQL, SQL ---> Hands-on exploratory and data visualization using Tableau and Power Bi ---> Ver Control - Git

Experience

Amazon

2 roles

Business Intelligence Engineer l (DE + DS)

Dec 2025 – Present · 3 mos · Bengaluru, Karnataka, India · On-site

Amazon Web Services (AWS)AWS cradleAWS LambdaAWS GlueAWS S3Amazon Redshift+7

Business Analyst (Data Science)

May 2022 – Mar 2025 · 2 yrs 10 mos · Bengaluru, Karnataka, India · On-site

1. Developed fully automated NSA (Next Slot Availability) bridge using Python,SQL, quick sight which helps to identify the gap between non-availability of next slot in slotted delivery of orders on Amazon Fresh. It also identifies the reason behind non-availability of the next slot to slotted delivery like capacity planning , Last mile delivery capacity , FC planning glitches.
2.Developed fully automated data pipeline for category wise products loading on vehicles from HUB to FC which helps to manage man power and other resources at FC and hub level. also helps to manage inventory capacity at BIN level in FC.
3. supply chain capacity planning in automated ways to reduce manual effort and time bound.
4.Developed fully automated tool in python to distribute orders hampered by weather or any event on particular slot and day to other slot and day such a way that it should not cross maximum orders or units for that particular day or slot and also maintain slot level curve.

DatabasesSQLPython (Programming Language)Business AnalyticsMachine Learning AlgorithmsData Analysis+3

Landmark group

Analytics Manager (Data Science)

Mar 2025 – Nov 2025 · 8 mos · Bengaluru · On-site

Led end-to-end pricing analytics and optimization initiatives across 6-7 Gulf countries for Landmark Group's Homecenter, delivering significant business impact through advanced machine learning solutions.
Key Achievements:
Comprehensive Pricing Strategy Implementation: Designed and deployed pricing solutions encompassing markdown processes, discounted pricing strategies, optimal pricing models, margin and revenue optimization, and price elasticity modeling across all Gulf markets.
Data Pipeline Architecture: Engineered a full-fledged, automated data pipeline to support ML-driven optimal pricing and price elasticity models, enabling real-time prediction of optimal price points to maximize revenue and margins.
Model Performance Excellence: Optimized machine learning models to achieve 70% accuracy with 65% adoption rate versus traditional planner inputs, demonstrating strong business confidence in AI-driven recommendations.
Operational Efficiency Gains: Reduced planning cycle time by 2-3 days through complete automation of the data pipeline and ML model outputs, enabling planners to directly consume insights for budgeted revenue planning and markdown allocation across all Gulf countries for each sales period.
Impact: Transformed pricing operations from manual, time-intensive processes to automated, data-driven decision-making, significantly improving both accuracy and efficiency while empowering commercial teams with actionable insights.

Data ScienceMachine LearningPython (Programming Language)sparkSQLPySparkAzure Databricks

Udaan.com

Data Scientist under credit management department

Feb 2021 – Apr 2022 · 1 yr 2 mos · Bengaluru, Karnataka, India

SQL developer ,
data analysis ,
dash board creation,
python developer and python automation,
machine learning model development,
statistical analysis for credit score,
building diffrent logistic regarding credit score,
monitoring and analysing credit scores and pitfalls

DatabasesSQLBusiness AnalyticsMachine Learning AlgorithmsData AnalysisAnalytics+2

Hurrey tech ventures

Data Scientist Associate

Jan 2021 – Feb 2021 · 1 mo · Bengaluru, Karnataka, India

1. Applying ML, AI to create a learning pathway.
2.Data visualization.
3.Development of Recommendation Engine.
4.Predictive modeling.

DatabasesSQLBusiness AnalyticsMachine Learning AlgorithmsData AnalysisAnalytics+2

Ineuron.ai

machine learning interns

Oct 2020 – Jan 2021 · 3 mos · Bengaluru, Karnataka, India

usecase1: developing a Recommendation system that will recommend the best freelancer to the client.
usecase2: customer segmentation as well as a freelancer segmentation.

DatabasesSQLBusiness AnalyticsMachine Learning AlgorithmsData AnalysisAnalytics+1