Data Science & AI Lead

About ArborKnotArborKnot Capital Partners is an investment firm specializing in consumer debt portfolios acrossAustralian and European markets. Data is the core of how we operate: every portfolio we acquire ispriced, monitored, and optimized by models our data team builds and owns. We are a small, seniorteam where your work reaches the investment committee, not a backlog.The roleYou will lead our data science function end to end. This is a hands-on leadership role: you own themodels that price every deal we do, the infrastructure that keeps them current, and the roadmap forwhere our modelling capability goes next. We are building an AI-native data function: AI tooling isload-bearing in how we work, and the next phase of our platform is an agentic layer that puts modeloutputs directly in the hands of the business. You will work directly with the VP Data and thecommercial team, and mentor the data scientists working alongside you.What you'll own▪ Production models. Two models in production today drive portfolio pricing and recoveryforecasting. You own their accuracy, their maintenance, and their evolution.▪ Retraining infrastructure. Build the pipeline that retrains our models on fresh data at a quarterlycadence or better, so every pricing decision reflects current portfolio behavior.▪ The feedback loop. Turn post-deal analysis into a systematic learning engine that sharpenspricing transaction by transaction.▪ The team. Mentor and grow the data scientists on the team; set the technical bar for how webuild.▪ The agentic AI layer. Design and build the tooling that lets portfolio managers query data, runscenarios, and get model outputs directly: agents, LLM workflows, and the governance that makesthem safe on real financial data.What you bring▪ 5+ years in data science with real production ML experience: models you built, deployed, and keptalive▪ Strong Python and SQL; comfortable owning pipelines, not just notebooks▪ Experience with cloud data platforms (we run on GCP and BigQuery)▪ Hands-on experience building with LLMs and modern AI tooling: you use AI daily in how you work,and you've shipped real workflows or features on top of it▪ Commercial instinct: you translate model outputs into decisions a non-technical stakeholder canact on▪ Ownership mentality: you close loops without being chased▪ Fluent English (our leadership and counterparties are international)Nice to have▪ Experience designing agentic systems or LLM-based products running in production▪ Background in credit risk, lending, collections, or debt purchasing▪ Survival analysis, forecasting, or propensity modelling experience▪ Experience leading or mentoring other data scientists