• Lead experimentation and model development for AI/ML solutions in legal products • Design and evaluate NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies) • Define agentic workflows and reasoning strategies for multi-step legal tasks • Define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality) • Analyze large-scale legal datasets to extract insights and improve model performance • Establish best practices for model evaluation, validation, and benchmarking • Translate experimental results into clear product recommendations and business impact • Collaborate with product, legal experts, and engineers to align solutions with user needs • Mentor team members and provide technical leadership in data science and AI

• Build and refine data pipelines for both structured and/or unstructured healthcare data. • Apply AI/ML models to identify patterns, predict trends, and extract meaningful insights from health datasets. • Work with the engineering team to source data and possibly integrate data models into day-to-day analytics. • Create visualizations and reports that translate data into clear stories for clinical and technical stakeholders.

Role Description We are looking for a passionate and driven Data Science Manager to join us in this exciting journey and support the definition and execution of Feedzai’s Product AI vision & strategy. The Data Science Manager role requires an engineer at heart who is able to lead and guide Data Science/Machine Learning teams to deliver Feedzai financial crime fighting products. The role requires deep data science knowledge allowing the teams to have strong support at the management level. Besides technical leadership, you will: - Hire top-class data scientists/machine learning engineers. - Plan the execution of product development driven by the product management team. - Manage and lead by example teams with a positive attitude bringing out the best of people. As Data Science Manager for the Product AI team, you will lead a team responsible for maintaining and building innovative solutions supporting our data and machine learning initiatives, namely the Feedzai IQ suite of products. In this role, you will work in mission-critical components of our stack, with the responsibility to meet stringent performance and reliability targets. Your leadership will ensure that our data scientists and engineers have the robust, scalable, and efficient tools they need to drive innovation and achieve our business objectives. Your Day to Day - Manage one or two teams of data scientists/machine learning engineers from daily execution to performance and career management. - Lead by example, care for your team, and establish credibility with the quality of your and your team's technical execution. - Provide technical leadership to the team from driving architecture, design, and experimental setups up to doing code reviews. - Be responsible for the planning, execution, and success of technical projects. - Work with key stakeholders across all groups within the Engineering, Product, Research, and Customer Success Teams. - Develop and empower top-class data science and technology practices in the teams. - Closely work with the recruiting team to find and interview data scientists. Qualifications - 2+ years of Team Leading and/or Management experience in managing technical projects and DS/ML teams. - 3+ years of experience in applied ML. - 5+ years of experience in data science. - Capable of leading by example not being afraid to take risks and going beyond what’s expected. Requirements - Experience working on customer-facing Data Science initiatives. - Experience working with real-time inference. - Experience working with distributed processing frameworks such as Spark. - Experience working on the fraud detection domain. Your First 30-Days at Feedzai You will be immersed in our brand with training, connections, and one-on-one time with your manager. You may shadow your colleagues virtually or onsite at an office depending on where you work as you are supported through your Feedzai journey. In addition, you will have access to a ton of information to give you history, context, and all the knowledge you can handle about Feedzai and the team. Finally, you will start working on projects and collaborating on work currently being done. We can't wait to have you join the team! Company Description Feedzai is the world’s first RiskOps platform for financial risk management, and the market leader in safeguarding global commerce with today’s most advanced cloud-based risk management platform, powered by machine learning and artificial intelligence. - Securing the transition to a cashless world while enabling digital trust in every transaction and payment type. - Trusted by the world’s largest banks, processors, and retailers to protect trillions of dollars and manage risk. - Improving the customer experience for everyday users, without compromising privacy. - Series D company with $282M raised to date and a valuation of $2 billion. - Technology protects 1 billion consumers and 90 billion transactions each year.

• Partner with stakeholders to define and deliver AI/analytics use cases, translating business needs into scalable data science solutions. • Design and develop machine learning models and analytical approaches to support search, discovery, and insight generation across structured and unstructured data. • Build and implement NLP, semantic search, and entity resolution capabilities to enable advanced information retrieval and relationship analysis. • Leverage document-based data (e.g., OCR/ICR outputs, metadata, and free text) to extract insights and support downstream analytics and search solutions. • Collaborate with data engineers to integrate models into production environments, including Palantir Foundry, Databricks, and AWS-based platforms. • Develop model evaluation frameworks, confidence scoring, and explainability approaches to ensure transparency and usability of AI outputs. • Support development of analytics, reporting, and dashboards to drive operational insights and decision-making. • Operate within an Agile delivery model, contributing to sprint planning, experimentation, and iterative solution delivery. • Communicate findings and recommendations clearly to both technical and non-technical audiences, including client stakeholders. • Contribute to solution design, proposal support, and thought leadership in AI/analytics capabilities.