Scrum Master – Data & Analytics (AI/ML Ops) at Compassx

<div><span style="text-decoration: underline;"><strong>About Us:&nbsp;</strong></span></div> <div>CompassX is a boutique business and technology consulting firm. We help Fortune 500 and high-growth clients deliver their most strategic initiatives, from enterprise transformations to digital and data-driven projects. With over 15 years of proven results, we’ve expanded across industries including financial services, pharmaceuticals, aerospace, consumer products, and quick service restaurants.</div> <div>&nbsp;</div> <div>We are honored to be recognized as a three-time winner of Consulting Magazine’s Best Boutique Firms to Work For, and previously recognized as a “Best Place to Work” in Southern California and one of INC.’s 5000 fastest-growing private companies in the U.S.</div> <div>&nbsp;</div> <div><span style="text-decoration: underline;"><strong>About the Role: </strong></span></div> <div>Our client, a pioneering biotechnology company, is seeking a dedicated Scrum Master – Data &amp; Analytics to enable high-performing Agile delivery with a specific focus on implementing AI/ML Ops practices. This role is central to the organization’s ambition to become a fully integrated biotech company by delivering governed, reliable, and scalable AI/ML solutions.</div> <div><br>You will serve as a "Player-Coach," partnering with Product Owners, technical leads, and vendors to manage a portfolio that includes data platforms, ML models, AI agents, and automation workflows.</div> <div><br>This role requires onsite preserence in Carlsbad, CA 3 days a week (Tues-Thursday).&nbsp;</div> Key Responsibilities: • Agile Delivery & Team Facilitation: • Serve as the Scrum Master for one or more Data & Analytics squads delivering use cases such as patient finding, trial optimization, and AI-assisted authoring. • Facilitate all core Agile ceremonies (sprint planning, daily stand-ups, retrospectives) ensuring they are purposeful and outcome-oriented. • Remove delivery impediments by coordinating across IT, security, and business partners. • AI/ML Ops Implementation: • Drive the adoption of AI/ML Ops practices, including version control, CI/CD for data and models, automated testing, and monitoring. • Partner with architecture leads to align team practices with modern data platform patterns (e.g., Databricks Lakehouse, RAG, agentic automation). • Ensure "Definition of Done" includes operationalization requirements like observability, lineage, and documentation rather than just the initial build. • Coaching & Continuous Improvement: • Coach Product Owners, Engineers, and Analysts on Agile principles, story writing, and flow-based metrics (throughput, cycle time, WIP). • Promote consistent use of IT Product Centric Framework (ITPCF) patterns and Jira standards. • Foster a culture of psychological safety, turning retrospective insights into concrete action items. • Governance, Compliance & Quality: • Ensure delivery practices support regulatory expectations (GxP/SOX) for data and AI in a life sciences context, including validation and audit trails. • Partner with Data Governance and Security to embed required controls (policy-as-code) directly into team workflows. Required Education & Experience: • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (Advanced degree or certifications like CSM, PMI-ACP, or SAFe preferred). • 5–8+ years in Agile delivery roles supporting data, analytics, or software engineering teams. • Hands-on experience implementing DevOps or MLOps practices (CI/CD pipelines, observability, incident response) for AI/ML workloads. • Experience in Life Sciences, Healthcare, or other regulated industries is strongly preferred. • Working knowledge of modern architectures (Lakehouse, vector search, semantic layers) and tools such as Databricks and Jira. Leadership Competencies: • A track record of enabling teams to self-organize and continuously improve. • Ability to simplify complex technical topics and align diverse stakeholders (R&D, Clinical, Commercial) on priorities. • A strong commitment to the ethical, responsible, and compliant use of data and AI.