16+ years of experience in IT and comprehensive industry knowledge on Data Science, Machine Learning, Generative AI, Data Warehousing and Data Visualisation & Analysis. Strong experience in Statistical Modelling and Mach…
16+ years of experience in IT and comprehensive industry knowledge on Data Science, Machine Learning, Generative AI, Data Warehousing and Data Visualisation & Analysis. Strong experience in Statistical Modelling and Machine Learning techniques such as regression, classification, clustering, deep learning, natural language processing and utilisation of appropriate statistical models to use in specific situations, with a deep understanding of the trade-offs between different models. Expert in predictive modelling, churn analysis, recommender systems, pattern recognition, segmentation, hyper parameter optimisation, multi-variate testing to deliver insights and implement action-oriented solutions to complex business problems.
Managed and supported data science team members by providing strategic direction, coaching, and mentorship. Scoped, designed, and implemented machine learning models to support the numerous initiatives of the business and demonstrated the impact to the bottom line of the business.
Strong experience in Statistical Modelling and Machine Learning techniques such as regression, classification, clustering, deep learning, natural language processing and utilisation of appropriate statistical models to use in specific situations, with a deep understanding of the trade- offs between different models.
Lead a team of data scientists (team size 7) to design, prototype, test, deploy and retrain predictive and prescriptive analytical models.
Developed and deployed a Generative AI chatbot using AWS Bedrock, integrating Claude Instant, Haiku, and Sonnet LLMs for comprehensive query handling.
Utilized Chainlit to create an intuitive GUI and implemented AWS Lambda functions for managing event-driven workflows, effectively fetching data from Amazon Redshift and logic from knowledge base.
Enhanced productivity by 20% through the innovative application of AI-driven root cause identification, improving operational efficiency and problem-solving capabilities.
Created predictive models using deep neural networks (DNN) with TensorFlow & Keras to forecast 4 critical quality parameters, achieving less than 10% MAPE during UAT for high consistency in production.
Implemented Feature Importance model using XGBoost and Random Forest algorithms to analyse intricate relationships between input and output variables and identify key factors influencing quality parameters, enhancing predictive accuracy and process optimization.
Utilized Graph Algorithms to map the hierarchy from raw material to final production output lab result, enabling comprehensive traceability and connection establishment within the production process.
Leveraged SHapley Additive exPlanations (SHAP) to enhance model interpretability by quantifying the impact of each input variable on the model's predictions, facilitating better understanding and transparency.
Worked directly with business partners to develop, communicate and execute the projects and provided strategic direction and took accountability for requirements, procedures and standards.
Developed solutions that bring critical insights to wide scale of different problems such as targeting customers and segmenting markets, product design, marketing optimization, demand forecasting and brand valuation, profit and price analyses and fraud detection.
Implemented advanced statistical analyses identifying trends, and exploring opportunities with the aim of generating actionable insights.
Developed NLP models for Text Classification & Sentiment Analysis.
Performed Text Classification and Sentiment Analysis for unstructured and semi-structured data and ensured low False Positive Rate of the model.
Identified and assessed available machine learning and statistical analysis libraries (including regressors, classifiers, statistical tests, and clustering algorithms).
Worked with NLTK, Gensim, Spacy, Keras & Tensorflow libraries to NLP data processing and identified patterns using Bag of words, TF-IDF, Word2Vec and LSTM techniques.
Categorized comments into positive and negative clusters from different social networking sites using Sentiment Analysis and Text Analytics.
Developed NLP models for Text Classification & Sentiment Analysis.
Performed Text Classification and Sentiment Analysis for unstructured and semi-structured data and ensured low False Positive Rate of the model.
Identified and assessed available machine learning and statistical analysis libraries (including regressors, classifiers, statistical tests, and clustering algorithms).
Worked with NLTK, Gensim, Spacy, Keras & Tensorflow libraries to NLP data processing and identified patterns using Bag of words, TF-IDF, Word2Vec and LSTM techniques.
Categorized comments into positive and negative clusters from different social networking sites using Sentiment Analysis and Text Analytics.
Designed & developed complex mappings with variety of complex transformations.
Provided data analysis and recommendations for the correction, enhancement and/or development of ad-hoc and canned end-user reports.
Performed analysis for a wide range of requests using data in different formats and from various platforms using Informatica.
Analysed user data to determine business rules and created logical and physical data models and documented functional, logical & feed specifications.
Coordinated with SMEs for dimensional modelling and metadata definition.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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