Technology with a Purpose. OCLC supports thousands of libraries in making information more accessible and more useful to people around the world. OCLC provides shared technology services, original research and community programs that help libraries meet the ever-evolving needs of their users, institutions, and communities. With office locations around the globe, OCLC employees are dedicated to offering premier services and software to help libraries.

The Senior Data Science Technical Manager is responsible for leading and mentoring a team of data scientists, engineers, and analysts in driving data-driven solutions across the organization. You will be responsible for managing the technical aspects of data science projects, ensuring the quality and accuracy of data analysis, and delivering actionable insights that inform strategic decision-making.

• Manage a team of data scientists, analysts, and engineers using agile management practices to plan, design and deliver data science solutions
• Manages multiple team efforts simultaneously from gathering data and documenting requirements specification, model development and evaluation, deliverable maintenance, and presenting measures of business impact.
• Collaborate with Data Science Director and members of Product and Delivery Lead teams to develop a global OCLC Data Science strategy and supporting program that aligns with the company’s goals and objectives
• Assist in managing Data Science project forecasting, roadmapping, and resourcing for sprints and quarterly planning
• Develop comprehensive knowledge of OCLC data structures and metrics, including product entitlement, utilization, support, pricing, revenue, sales, and marketing activities.
• Empower team members to make technical decisions independently, but make final decisions when necessary
• Draft quarterly data science OKRs and KPIs; generate and implement data science process improvements
• Recruit and mentor members of a high-performance, proactive Data Science team who act as pioneers in the Data Science space and lead the onboarding effort of new team members
• Design and conduct interviews for candidates (examining both technical skills and soft skills); train team members to execute technical interviews
• Foster team members’ skill development and professional growth through technical guidance, coaching, creating career development plans, delivering regular feedback and managing performance/productivity
• Hold regular 1:1 meetings with direct reports
• Maintain empathy for the team by keeping awareness of engineering processes and practices by, for example, evaluating individual workflow during one on ones, conducting code reviews, or contributing to technical project work

• Master’s degree in a quantitative field (Mathematics, Computer Science, or Statistics, for example) and 8+ years professional experience in a data science role with 3+ years in a technical lead or management role or PhD in a quantitative field and 6+ years in a data science role with 1+ years in a technical lead or management role
• Expert proficiency in a scripting language such as R or Python, including Python data libraries (numpy, pandas, matplotlib, scikit-learn)
• Expert proficiency in a low-level or performant language (e.g. C or Golang)
• Expert proficiency in working within a cloud computing environment using software development best practices
• Experience automating production-quality statistical or machine learning models at scale with expert understanding of their underlying mathematical and statistical theory
• Proficiency in MLOps tools for deploying, monitoring, and maintaining machine learning or statistical models (e.g. Amazon SageMaker, Azure ML, or Databricks)
• Experience leading strategic projects and large initiatives spanning multiple teams, roles, and functions demonstrating effective cross-functional relationships
• Demonstrates progressive experience in a leadership role with current technical experience
• Demonstrates excellent communication skills with ability to explain statistic and mathematical concepts to non-experts
• Demonstrates the ability to decompose large, complex problems into smaller components and delegate tasks to team members based on individual expertise and experience