Enabling safe and rewarding digital lives for genuine people, everywhere We make it our mission to ensure more genuine people have digital access to opportunities, and businesses have access to more genuine people. Our technology draws on diverse and reliable data to create a single point of truth for identity and address verification. With over 30 years of experience behind us our team and technology are focused on enabling safe and rewarding digital lives for everyone. Regardless of age, location or background, genuine people everywhere should be able to digitally prove who they are and where they live. About the team and role Data Scientist – Fraud Analytics & Technical Writing Join GBG’s Go‑to‑Market Data Science & Analytics team, a newly established, high‑impact function shaping how we demonstrate value to customers and empower internal teams with actionable insights. As a Data Scientist – Fraud Analytics & Technical Writing, you’ll analyze large, complex datasets to surface fraud patterns, translate findings into clear business narratives, and create high‑quality technical documentation that standardizes methods and accelerates adoption across the organization. You’ll partner cross‑functionally with Sales, Product, and Operations, design dashboards that communicate trends, and influence roadmap and strategy—while building scalable, automated processes that elevate decision‑making and customer outcomes What you will do Fraud Detection & Analysis - Analyze large, complex datasets to detect patterns, anomalies, and emerging fraud trends - Collaborate with internal teams to validate findings and refine detection strategies - Translate key findings into clear, compelling insights that demonstrate solution value to prospective customers - Support the development of standardized frameworks to quantify business impact across customer profiles   Technical Documentation - Create and maintain high-quality technical documentation, including methodologies, workflows, and system processes - Translate complex analytical findings into clear, actionable insights for both technical and non-technical audiences - Ensure documentation is standardized, accurate, and easily accessible for internal teams   Collaboration & Reporting - Work closely with cross-functional teams to implement data-driven solutions - Design dashboards and reports to communicate fraud trends and detection results effectively - Provide regular updates and recommendations to stakeholders based on data-driven findings

• Directly execute complex end-to-end data science projects, including statistical modeling, machine learning, and predictive analysis. • Partner with Engineering/IT to define requirements for and, where necessary, personally build and maintain robust data pipelines, data marts, and analytics tools to support the team's work. • Establish and enforce technical best practices, code review standards, and documentation guidelines to ensure the reliability and reproducibility of all data products. • Lead and mentor our existing Data Analyst, providing regular coaching, setting performance goals, and facilitating career development. • Play a primary role in recruiting, interviewing, and onboarding new talent as the data team scales. • Promote a culture of data literacy and continuous learning within the Data Team and across the organization. • Define and articulate a compelling data strategy and roadmap for the department over the next 1-3 years, aligning data initiatives directly with company OKRs and business needs. • Act as the technical Product Owner for the Data Team's backlog. Manage the end-to-end lifecycle of all data projects, ensuring timely delivery, managing scope, and communicating progress to stakeholders. • Collaborate with executive leadership and cross-functional teams (Product, Marketing, Operations) to identify high-impact analytical opportunities and translate ambiguous business questions into testable data hypotheses and clear deliverables. • Establish foundational principles for data governance, integrity, privacy, and security within the department.

• Collaborate with the product and engineering team to identify areas for automation and improvement • Designing and developing state-of-the-art NLP algorithms, with a focus on orchestrating LLMs across various providers (OpenAI, Anthropic, Google, etc.) to optimize for cost, latency, and accuracy. • Analyse data and conduct experiments to improve the accuracy and efficiency of models • Build and deploy models that can be integrated into production applications • Evaluate emerging LLM tools and frameworks to maintain a competitive edge in research automation • Collaborate with leading ML practitioners in the research synthesis space to fundamentally change the way the world derives accurate insights from global research output

• Partner with cross-functional teams - including product management, design, engineering, research - to support product development efforts • Experiments: design and measure experiments to inform feature decisions • Develop key strategic insights through exploratory data analysis, to inform future investments or pivot in strategy • Build scalable metrics and dashboards to empower efficient decision-making at Nextdoor • Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team-building exercises • Build in-person relationships with team members and contribute to Nextdoor's company culture