• Spearheaded key business strategic engagements in Ad Personalisation, designed and delivered roadmap which led to 14% increase in attributed GMV and subsequent growth of the applied science capabilities in Zalando Marketing Services.
• Led a cross-functional team of 11, designed and implemented recommendation systems accounting for 16% increase in the number of user clicks.
• Established machine learning operations and infrastructure capabilities to support low latency, high throughput, near real-time predictions achieving 50% reduction in latency.
• Initiated collaborations with the Search and Discovery teams to improve the ads candidate selection and filtering process using CLIP (by Open AI), initial proof-of-concept suggests an uplift in ads fill rate and improved search offline rankings metrics.
• Developed and established the "Research, Development & Productionisation Process" as a guide to optimise and accelerate the path from solution ideation to production.

• Led team of 5 and build ML recommendation engine for audience targeting (campaign ads) increasing website purchase rate, estimated to drive £12MM in annual gross transaction value.
• Headed the development of a series of classification conversion propensity models, scoring customers who are likely to purchase a product, increasing purchasing rate by 10%.
• Designed software pipelines to automate social media advertising processes and productionised regression and classification lookalike models for influencer marketing.
• Worked closely with Product Managers to identify business opportunities, liaised with marketing stakeholders and developed a roadmap on-boarding 4 new key strategic initiatives, estimated to drive annual business growth by 20%.
• Internally recruited senior data scientists and machine learning engineer to meet capacity needs and demands of the expanding roadmap.

• Built a ML time-series forecasting pipeline for retail banking. The productionised and automated ML process was adopted across three banks (Lloyds, Halifax and Bank of Scotland).
• Directed proof-of-concept for managing the bank's liquidity funds by utilising the python pipelines and libraries created for retail banking and obtained £5MM funding for scaling up.
• Designed early warning machine learning classification system for the commercial banking credit risk division, resulting in reducing the impairment of its portfolio.
• Established the Data Science Advanced Development Program for the Chief Data Office, a comprehensive data scientist training program for graduates and experienced hires.
• Recruited junior data scientist for the graduate scheme increasing the number of the data science team by 15% annually.

• Run end-to-end solution from data capture, to developing medical imaging models and algorithms. Deployed the solution in NHS clinic to monitor brain function and predict impairment in patients with severe psychiatric conditions.
• Led a team of 10 people (data engineers, developers, and computational psychologists), launched the project and pioneered the use of the 1 st portable brain-imaging device in the developing world.
• Developed imaging device to predict brain impairment in paediatric intensive care patients, used to aid surgical interventions in a population 80% of which would otherwise suffer from brain injuries.