Job
Description
Role name : Scrum Master ( AI & Data Science), AI/ML Scrum Master , Technical Scrum Master – Data & AI Years of exp : 5 - 8 yrs About Dailoqa Dailoqa’s mission is to bridge human expertise and artificial intelligence to solve the challenges facing financial services. Our founding team of 20+ international leaders, including former CIOs and senior industry experts, combines extensive technical expertise with decades of real-world experience to create tailored solutions that harness the power of combined intelligence. With a focus on Financial Services clients, we have deep expertise across Risk & Regulations, Retail & Institutional Banking, Capital Markets, and Wealth & Asset Management. Dailoqa has global reach in UK, Europe, Africa, India, ASEAN, and Australia. We integrate AI into business strategies to deliver tangible outcomes and set new standards for the financial services industry. Working at Dailoqa will be hard work, our environment is fluid and fast-moving and you'll be part of a community that values innovation, collaboration, and relentless curiosity. We’re looking at people who : Are proactive, curious adaptable, and patient Shape the company's vision and will have a direct impact on its success. Have the opportunity for fast career growth. Have the opportunity to participate in the upside of an ultra-growth venture. Have fun 🙂 Don’t apply if: You want to work on a single layer of the application. You prefer to work on well-defined problems. You need clear, pre-defined processes. You prefer a relaxed and slow paced environment. Our Philosophy Small team : Small talented teams outperform large and slow-moving companies. We avoid bureaucracy, keep meetings to a minimum and focus on creating value. Simple where possible: We are passionate about new technology (in particular Machine Learning and AI), but we are more passionate about solving problems for our customers. We strive to find the best solution, be it cutting-edge or old-school. Customer obsessed: We take every opportunity to talk to our customers. We obsess over their problems and work every day to make them happy. Role Overview As a Scrum Master at Dailoqa, you’ll bridge the gap between agile practices and the unique demands of AI/ML-driven product development. You’ll coach cross-functional teams of software engineers, data scientists, and ML engineers to deliver high-impact solutions while fostering a culture of collaboration, experimentation, and continuous improvement. Key Responsibilities Agile Facilitation & Coaching Facilitate all Scrum ceremonies (sprint planning, daily stand-ups, reviews, retrospectives) with a focus on outcomes, not just outputs. Coach team members (software engineers, AI/ML engineers, data scientists) on Agile principles, ensuring adherence to Scrum frameworks while adapting practices to AI/ML workflows. Sprint & Workflow Management Manage hybrid sprints that include software development, data science research, and ML model training/deployment. Maintain Agile boards (Jira, Azure DevOps) to reflect real-time progress, ensuring transparency for stakeholders. Monitor sprint velocity, burndown charts, and cycle times, using metrics to identify bottlenecks and improve predictability. AI/ML-Specific Agile Leadership Adapt Agile practices to AI/ML challenges: Experimentation: Advocate for “spikes” to validate hypotheses or data pipelines. Uncertainty: Help teams embrace iterative learning and fail-fast approaches. Cross-functional collaboration: Resolve dependencies between data engineers, MLops, and product teams. Continuous Improvement Lead retrospectives focused on both technical (e.g., model accuracy, pipeline efficiency) and process improvements. Drive adoption of Agile engineering practices (CI/CD, test automation) tailored to AI/ML workflows. Qualifications ( Must-Have ) 5–8 years as a Scrum Master, with 2+ years supporting AI/ML or data science teams . Deep understanding of Agile frameworks (Scrum, Kanban) and tools (Jira, Azure DevOps). Proven ability to coach teams through AI/ML-specific challenges: Model lifecycle management (training, validation, deployment). Balancing research-heavy work with delivery timelines. Managing data dependencies and computational resource constraints. Certifications: CSM, PSM, or equivalent. Strong understanding of Agile frameworks (Scrum, Kanban) and SDLC principles Experience working with cross-functional teams including data scientists and AI engineers Exposure to AI/ML product development cycles, including research-to-production workflows Familiarity with AI project elements such as model training, data labeling, GenAI experimentation, or MLOps Show more Show less
