Hi, I'm Muhammed Hisham
Data Scientist

I design and build advanced dashboards and machine learning use cases, including Power BI dashboards, customer segmentation, and advanced analytics, with a focus on practical implementation of cutting-edge technologies in the Retail domain.

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About Me

Muhammed Hisham

Iā€™m a Data Scientist with hands-on experience solving real-world business problems in the Retail Industry through data-driven decision-making.

Proficient in tools and technologies including Python, PySpark, SQL, and Power BI, with a strong focus on handling large-scale datasets and uncovering actionable insights.

My expertise lies in regression modeling, demand forecasting, inventory management, and customer segmentation, along with a solid foundation in data wrangling, EDA, feature engineering, data visualization, and ML model development.

Passionate about continuous learning and always eager to take on challenging roles to deepen my expertise in data science and applied machine learning.

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Domain Expertise: Retail

As the sole Data Scientist managing the end-to-end analytics across 140+ retail stores, along with 10+ brands and wholesale operations, I specialize in building scalable, high-impact data solutions that drive business performance at scale.

šŸ§‘ā€šŸ¤ā€šŸ§‘ Customer Segmentation

Built customer profiling and clustering models across all stores to enable personalized marketing and improve retention.

šŸ“¦ Inventory Optimization

Analyzed multi-brand inventory flows to reduce overstock, stockouts, and aging across retail and wholesale channels.

šŸ“ˆ Sales & Demand Forecasting

Created demand forecasting models tailored for individual outlets, brands, and product categories using historical data.

šŸ“Š Retail KPIs & Reporting

Automated reports to monitor key retail KPIs such as Sell-Through Rate, Inventory Turnover, and Gross Margin Return on Investment (GMROI).

šŸ§  Scalable Dashboarding

Designed centralized Power BI dashboards with filters for brand, store, and region ā€” enabling leadership to make real-time decisions.

šŸŒ Cross-Domain Collaboration

Worked across sales, supply chain, and finance to translate business needs into production-ready data science solutions.

My Expertise

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Customer Segmentation

Built clustering models to group customers for targeted marketing and campaign optimization.

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Dashboards

Created interactive dashboards in Power BI to monitor sales, inventory, and operational KPIs.

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PySpark

Utilized PySpark to process large datasets efficiently and enable scalable data pipelines.

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Power BI

Developed rich visualizations and reports tailored to business users and retail executives.

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Inventory Management

Created analytics tools to minimize stockouts, overstock, and aging inventory in retail stores.

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Data Analysis

Performed EDA and statistical analysis to identify trends, patterns, and business opportunities.

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Python

Used Python for data cleaning, model development, automation, and business logic integration.

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Forecasting

Developed demand and sales forecasting models using historical trends and ML algorithms.

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Machine Learning

Implemented ML algorithms for classification, regression, and clustering use cases.

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ETL & Automation

Automated data workflows using scheduling scripts and optimized delivery to dashboards.

Education

2020 - 2023

BCA Robotics Machine Learning & Artificial Intelligence

Completed my Bachelor of Computer Application degree with a focus on cutting-edge information technology concepts and applications. During my academic journey, I developed strong foundations in:

  • Artificial Intelligence & Machine Learning
  • Data Structures & Algorithms
  • Natural Language Processing
  • Computer Networks
  • Database Management Systems
  • Web Development Technologies

Participated in numerous technical workshops and hackathons, enhancing my problem-solving abilities and collaborative coding skills while working on real-world projects.

Professional Experience

September 2023 - Present

Junior Data Scientist

Nesto Technologies
  • Business Insights & Analytics: Delivered actionable data models and insights across all companies within the parent organization, Western International Group, driving business growth and operational efficiency.
  • Customer Segmentation: Implemented clustering techniques to segment customers and tailor marketing strategies, resulting in improved engagement and targeted outreach.
  • Inventory Optimization System: Built a data-driven Inventory Management Application to reduce stockouts, overstocking, and aging inventory issues across retail outlets.
  • Forecasting Models: Developed Sales and Demand Forecasting models using historical data from multiple sources to assist in planning and reduce storage and holding costs.
  • Business KPIs: Introduced and automated tracking of key performance indicators such as Sell-Through Rate, Inventory Turnover Ratio, and others to help business units make data-informed decisions.
  • Data Automation & Delivery: Scripted and scheduled daily ETL processes to feed web-based data visualizations, achieving up to 80% higher performance efficiency compared to legacy SAP BW systems.
  • Dashboard Development: Designed and maintained interactive dashboards using tools like Power BI or web-based platforms to address business-specific data visualization needs.
  • Big Data Environment Setup: Contributed to the initial setup and deployment of an on-premise Big Data environment, enabling scalable data handling and future ML model integration.
Customer Analytics Retail Analytics PySpark Bigdata Power BI Business Insights Sales Forecasting Demand Forecasting
April 2022 - July 2022

Machine Learning Intern

Cognitive Solutions
  • Data Cleaning & Preprocessing: Handled raw datasets by performing missing value imputation, encoding categorical variables, normalization, and feature engineering using Python libraries like Pandas and NumPy.
  • Exploratory Data Analysis (EDA): Visualized data distributions, correlations, and patterns using tools like Matplotlib and Seaborn to derive meaningful insights.
  • Model Building: Implemented and evaluated various machine learning algorithms including Linear Regression, Decision Trees, and K-Nearest Neighbors using Scikit-learn.
  • Model Evaluation: Measured model performance using accuracy, precision, recall, and confusion matrix, and fine-tuned hyperparameters for better accuracy.
  • Project Documentation: Documented the workflow, model pipeline, and key findings as part of final academic submission and presentation.
Python Pandas NumPy Matplotlib Seaborn Scikit-learn EDA Data Cleaning ML Algorithms

Featured Projects

Customer Segmentation

Customer Segmentation

Developed a customer segmentation model using clustering algorithms to categorize users based on purchase behavior and demographics for targeted marketing.

Python K-Means PySpark Power BI
View Details
Inventory Optimisation

Inventory Optimisation

Built a data-driven inventory management system to reduce stockouts, overstock, and aging inventory using forecasting and classification models.

PySpark Power BI Forecasting Retail Analytics
View Details
Retail Fraud Detection

Retail Fraud Analytics

Built rule-based anomaly detection to flag and report non-organic billing (splitting, store crossover, timing anomalies), resulting in updated fraud-prevention policies and lower promotional abuse

PySpark Power BI Anomaly Detection Retail Analytics
View Details
Email Spam Filtering

Email Spam Filtering

Built a classification model using NLP techniques to filter spam emails based on text features and improve email system security and performance.

Scikit-learn Naive Bayes NLP Python

Get In Touch

I'm currently looking for new opportunities to apply my Data Science skills. Whether you have a question, a project idea, or just want to connect, I'd love to hear from you!

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Email

m.hishamds@gmail.com

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Phone

+91 97445 42503

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Location

Villiappally, Kozhikode, Kerala, India, 673542

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