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

CarlsbadFull-Timemid

Data ScienceOtherScrum MasterProject & Program ManagementData & Analytics

0 views0 saves0 applied

Apply Now

Quick Summary

Requirements Summary

Coach Product Owners, Engineers, and Analysts on Agile principles, story writing, and flow-based metrics (throughput, cycle time, WIP).

Technical Tools

Data ScienceOtherScrum MasterProject & Program ManagementData & Analytics

About Us:

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.

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.

About the Role:

Our client, a pioneering biotechnology company, is seeking a dedicated Scrum Master – Data & 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.

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.

This role requires onsite preserence in Carlsbad, CA 3 days a week (Tues-Thursday).

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.

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.

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.