Lead Product Data Scientist

At Gradient Labs , we're building the AI customer operations platform for financial services. Founded in 2023, we now work with some of the biggest names in banking and fintech. Our platform runs specialist agents, purpose-built for financial services, to eliminate manual work across customer support and back-office operations. Together, they give product and operations teams the visibility and control to trust every outcome. We're a team of builders from companies like Monzo, Wise, Revolut and Google. If you're excited to tackle some of the hardest problems in AI and help shape the future of customer operations, we'd love to hear from you. 🎯 How you’ll make an impact This is a role where you’ll own opportunities and outcomes all the way from conversations with customers to testing hypotheses, running experiments, and proposing and delivering optimisations in our agent. You will: Be at the frontline of our product - talk to customers and align directly on what success looks like and how it’s measured. You’ll use raw, real-world data to form clear, actionable insights. Directly optimise the performance of our agent, tuning and improving it against those metrics for every customer we onboard. Own the optimisation flow end to end - you’ll use data to translate opportunities into tangible improvements in our agent, and close the loop by delivering and demonstrating that value. Get obsessive with the data: understand the data at the lowest level, then leverage this to form and test robust hypotheses about the bigger picture. Work across multiple teams and functions to bring shared understanding of where the highest impact opportunities are and how we deliver on them. Own your work end to end and scope your own initiatives - you'll be given real trust and independence, not a ticket queue. Turn ad hoc analyses and findings into powerful, scalable tooling for teammates and customers to self-serve. 💡 What you’ll bring Significant data science experience at a lead/staff level; building robust data pipelines is second nature, you’re fluent in SQL and Python, and have a strong understanding of statistical methods. A background working in a startup or a fast-moving tech environment, close to the product or customer side of the business. A knack for solving data puzzles and going from SQL queries to clear conclusions and next steps. A strong product mindset and pragmatic approach - you understand the right tradeoffs to make and can move fast to deliver product and business impact. Expert communication skills; this role will be partially customer-facing. Confident using AI to unlock efficiencies in your day-to-day while maintaining a high standard of output. Why join Gradient Labs ? This is a unique chance to be part of a team working with cutting-edge technology to reshape how businesses will operate in the future. Over the next 10 years, every company will need to embrace AI-powered operations to stay competitive, and this role puts you right in the middle of that transformation. You’ll tackle challenging and new problems, work with some of the most exciting brands across different industries, and be surrounded by a passionate, smart team that’s driven to build something groundbreaking. Benefits & Logistics 🧡 We’re still at early stages of building out our compensation bandings, whilst we continue to shape this, we’re open to chatting with people who have a range of salary requirements Our compensation package has two key components - base salary & meaningful equity Private medical & dental insurance 25 days holiday + bank holidays (or bank holiday opt out for 32 days holiday) Team socials and offsites Flexible working - we have an office in central London and a hybrid working approach. This role is open to London based or remote in the UK folks (ideally you'd be able to come into the office at least once per week) The Interview Process 📝 30 mins Talent Screen with our Founding People & Talent 45 mins First Stage interview with the Hiring Manager, our Founding Data Scientist Take Home Task 1 hr Task Deep Dive interview with our Founding Data Scientist and CTO 45 mins Final interview with our Chief Scientist or CEO Originally posted on Himalayas