ML-focused technical product manager for FSx for Lustre, a managed high performance file system used for distributed model training and large-scale batch inference. Customers include leading AI research labs at the cutting edge of generative AI.

Responsible for all aspects of Cloudera’s on-premises machine learning offerings. Developed the 3-year plan for Cloudera’s rearchitected private cloud ML platform; secured alignment of engineering, support, sales, and c-suite.

Responsible for all aspects of Cloudera’s offering relating to machine learning model development, production serving, and operations (MLOps). Later increased scope to include all on-premises machine learning products.- Managed scoping, development and launch of Applied ML Prototypes, a feature that allows Cloudera and its customers to develop and publish complete ML projects that decrease time to value for data scientists. Over 1000 unique projects launched using the feature within first 3 months. Loved by field and customers; highlighted in Cloudera earnings call.- Collated customer feedback, use cases and requirements to demonstrate the case for prioritizing development of a public API for our product. Managed scoping, development, beta program, and GA launch of a holistic product API.- Took a new private cloud machine learning platform from 0 to 1, relentlessly unblocking and building trust with our first paying customer, later our first public reference.

Led and managed a team of 7 full-time employees and a varying number of contractors, all focused on building machine learning solutions at big data scale for Cloudera customers.• Proposed and successfully advocated for a new machine learning focused organization within Cloudera Professional Services. Developed vision and operating plan. Successfully recruited founding team.• Developed go-to-market for expanded ML services offering. Trained field teams to identify and qualify opportunities.• Acted as player coach, guiding and mentoring team members through the course of dozens of projects. Personally led 2 strategic consulting projects to review clients’ overall machine learning platform architecture.

Led the Professional Services Specialization in Machine Learning. Helped customers leverage Cloudera’s big data platform and associated tooling to achieve business value through data science and machine learning solutions.• Re-architected a production machine learning solution to reduce anomaly detection delay from 4 hours to <30 minutes, significantly reducing costs due to lost production. Used Spark and Apache Arrow to enable parallelization of full pipeline.• Designed and evangelized best practices for production machine learning solutions on Cloudera’s platform, for both batch and near real-time solutions, including key considerations for choosing between architectures.• • Re-architected a production machine learning solution to reduce anomaly detection delay from 4 hours to <30 minutes, significantly reducing costs due to lost production. Used Spark and Apache Arrow to enable parallelization of full pipeline.• Designed and evangelized best practices for production machine learning solutions on Cloudera’s platform, for both batch and near real-time solutions, including key considerations for choosing between architectures.

Helped customers leverage Cloudera’s big data platform and associated tooling to achieve business value in a post-sales consulting role, with a focus on data science and machine learning.• Consistently successful projects with positive customer feedback, leading to increasingly high visibility assignments.• Led the migration of the then-largest Cloudera Data Science Workbench customer from a competitor tool, including architecting overall approach, automating migration, adapting specific Python/R solutions to the new environment, and educating users on best practices. 200+ users and 100+ active projects successfully migrated in under 4 months.

At Capgemini Consulting, a global digital strategy and transformation consulting company, I helped clients address business challenges using big data solutions, maintaining an MVP-first approach through discovery, alpha and beta, prioritizing features with high impact and low implementation effort to realize value early. Specific achievements included:• Led a team of 5 to develop a self-service BI reporting capability to provide the UK government with real-time statistics on the roll-out of its flagship Tax Free Childcare policy and inform ministerial decision making. Liaised with client-side stakeholders to clarify and prioritize requirements, translating high level user requests to actionable development tasks. Transformed data from multiple sources in a Hadoop data lake into business friendly data structures presented in a Pentaho BA web interface by creating robust ETL flows. Deployed on schedule to excellent user feedback.• Developed a risking service to automatically identify fraud and non-compliance for a government department using data from multiple government sources to cross-check submitted information and evaluate risk factors. Involved client-side stakeholders to design a system that prioritized cases based on a combination of value and risk, with the flexibility to adjust weightings based on campaigns or new insight, and tested with synthetic data to prove the solution’s suitability.

At Quick Release, a rapidly growing start-up specializing in Product Lifecycle Management (PLM) and data management, I applied a versatile skill-set in many capacities to expand and mature the business, focusing primarily on:Technical & Data Expertise• Primary resource to sales, management, finance, and project delivery teams on hundreds of data-driven challenges.• Technical expert for client projects with Ford, Rolls Royce, McLaren, Aston Martin and Jaguar Land Rover.Product Management• Owning the vision for software to improve efficiency in data collection, data management and automated reporting.• Setting strategy and direction for the Special Projects business function, a wider team of developers working on custom business software to assist clients and enhance QR’s services. Consultancy• Working with clients to improve PLM processes, focusing on data quality and reducing lost engineering time.• Working with clients pre-sales to understand requirements and shape engagements.