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Waseem Shammut

@waseemshammut

Data scientist and machine learning consultant whose trading research compared four classification models and evaluated predictions by strategy profitability.

Turkey

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In my freelance machine learning research, I studied whether trades would be profitable, analyzing approximately 750 candidate features and comparing XGBoost, LightGBM, CatBoost, and Logistic Regression. I used SHAP and permutation importance to assess feature contributions and designed an evaluation metric based on cumulative strategy profitability.

At Yield App, I designed and implemented a company-wide data warehouse supporting operational, financial, compliance, and customer analytics. I also developed data quality controls and QA processes that achieved 99% reporting accuracy, and built automated financial reporting pipelines.

At Nestlé Middle East, Syria & Iraq, I led the design and automation of sales performance dashboards and implemented customer segmentation and channel classification models. I also managed trade-spend analysis and supported data-driven sales planning.

As an independent consultant, I deliver analytics solutions for SMEs across retail, logistics, and food, from requirements gathering through delivery. I also built a containerized cryptocurrency ETL pipeline using Python, PostgreSQL, Prefect, Docker, and GitHub Actions.

Experience

Work history, roles, and key accomplishments

Current

Independent Data & Analytics Consultant

Current

Self Employed

Jan 2018 - Present (8 years 9 months)

Delivered analytics solutions and custom reporting tools for SMEs across retail, logistics, and food sectors. Built ETL pipelines, reporting layers, analytical data models, and Power BI dashboards, and led client engagements from requirements gathering through solution delivery.

ETL Data Modeling Power BI SQL Python Requirements Gathering Client Communication CRM Design Inventory Management

Freelance Data & Machine Learning Consultant

Freelance

Aug 2025 - Dec 2025 (4 months)

Conducted machine learning research for binary classification of profitable trades, analyzing 750 candidate features and developing models with XGBoost, LightGBM, CatBoost, and Logistic Regression. Applied SHAP and permutation importance for feature selection and model interpretability.

Machine Learning Classification Feature Engineering Feature Selection SHAP Permutation Importance XGBoost LightGBM CatBoost Logistic Regression Time Series Modelling Ensemble Learning Imbalanced Data Model Evaluation Unsupervised Learning Python Pandas NumPy scikit learn

Senior Data Analyst

Yield App

Oct 2022 - Oct 2024 (2 years)

Designed and implemented a company-wide data warehouse, developed data quality controls achieving 99% reporting accuracy, and built automated financial reporting pipelines. Developed executive dashboards, predictive models for customer behavior, and a customer onboarding journey funnel.

SQL Python Data Warehouse Data Quality QA ETL Power BI KPI development Predictive modelling Customer Segmentation Customer Journey Analytics AML Compliance Executive Dashboards Self Service Analytics

Sales Analytics Lead

Nestlé Middle East

Apr 2011 - Sep 2018 (7 years 5 months)

Led design and automation of sales performance dashboards, drove sales forecast reviews, and managed trade-spend analysis. Implemented customer segmentation and channel classification models, introduced data governance practices, and designed sales-force incentive schemes.