In my current role at LRQA, I lead the development of scalable, data-driven tools and products that support responsible sourcing and supply chain due diligence.
A core part of my role involves leading the integration, analysis, and development of grievance mechanism data collected across 11 helplines worldwide—empowering companies to identify emerging risks, support effective remediation, and strengthen their human rights and ESG strategies.
Through this work, I actively use data to amplify marginalised voices and enhance equity in access to remedy and protection within global supply chains.
My technical expertise includes identification of business and data requirements, developing data strategies, and managing data science projects through their complete life cycle. I am skilled at model calibration, model and process optimisation (Bayesian, parallel computing, process automation), hyper parameter tuning, and validation against independent datasets in Python.
I have proven success in effectively communicating high-quality, data-driven insights to technical and non-technical stakeholders.
I’m passionate about leveraging data for social good and committed to building inclusive, accountable systems through evidence-based approaches.
I am eager to apply my data skills with stakeholders across various sectors to tackle complex challenges and contribute to impactful, effective, and tangible solutions.
I am available for short-term projects and longer-term engagements.
In my pursuit of impactful projects, I prioritise initiatives which:
Benefit a large number of individuals
Maximise the size of the positive effects per person
Create long-term, self-sustaining positive change
