Built the data science function at Chamko — embedding machine learning capabilities directly into the core product, transforming influencer selection from a gut-driven process into a data-driven one, and presenting campaign analytics to executive stakeholders.
Building AI Capabilities in the Core Product
Built a variety of machine learning capabilities into the core product and contributed to the definition of key performance indicators for data gathering. Established the data infrastructure needed to support model training pipelines, feature stores, and automated reporting for the influencer marketing platform.
Cross-Team Collaboration & Onboarding Optimisation
Collaborated with multiple teams to gain a comprehensive understanding of the end-to-end user experience and developed strategies for improving the onboarding process. This work included age and gender prediction models (Keras) used to better match influencers to campaign demographics during onboarding.
Predictive Analysis & Influencer Recommendation
Transformed influencer enrollment into a data-driven process by building a recommendation system for influencer selection — matching brands to creators based on audience fit, engagement patterns, and historical campaign performance. Developed forecasting models to increase campaign profit margins and created features for accessing broader influencer data points. Presented campaign analytics and model outcomes directly to executive stakeholders.