Ahmed Bakir

My path to data science brought together two things. Economics, and later my MBA, gave me a grounding in applied statistics. Ten years of delivering ERP, CRM and business intelligence projects taught me the rest: how business processes really work, where clients feel the pain, why IT projects struggle, and how the systems behind them fit together. Data science, where mathematics, programming and business meet, was where both came together.

In late 2012 I started again at the ground level: studying the algorithms in depth, learning Python, R and Matlab, and searching for the business problems they could solve. The market was young and the move was a risk, but it was also the most enjoyable learning of my career.

In 2014 I delivered my first production project, a recommendation engine for one of the region's largest retailers. Since then I have built machine learning applications across sectors and countries, and more recently generative AI solutions in financial services and the public sector. I still start every project the way I started then: understand the business first, then let the data show what is possible.

Data science and machine learning

statistical analysis, regression, classification, clustering, forecasting, neural networks, natural language processing, recommender systems

Generative AI and agents

retrieval-augmented generation (RAG), vector databases, LangChain, AI agents

Data and engineering

Python, SQL, R; data pipelines, validation and monitoring, CI/CD; AWS, Microsoft Azure, Google Cloud; Power BI, Tableau, Looker

Enterprise systems

ERP, CRM and business intelligence implementation

Strategy and leadership

data and business strategy, team leadership, stakeholder management, project management

Built and running in production: recommender systems, chatbots, price and assortment optimisation, credit scoring, an AI financial adviser, an algorithmic trading agent, analytics engines.

Languages: English, Arabic, French, and learning Spanish.