Oclc
SeniorDataScientist
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Scientist at Oclc. Skills: machine learning models, statistical algorithms, data pipelines, MLOps, Python, SQL, Snowflake, AWS, Azure. Design, develop, and deploy advanced machine learning models and statistical algorithms. Conduct rigorous statistical analysis, validate hypotheses, and provide actionable insights”
What You'll Achieve.
drive business solutions; drive data-driven decision making; quantify improvements in terms of business efficiency or customer experience; drive strategic business impact
Industry & Context.
problem-solve; solve complex business problems; solve complex and highly impactful quantitative business problems
What They're Looking For.
Must Have
Master's Degree in Mathematics, Computer Science, or Statistics or related quantitative fields and 5+ years professional experience in a data science role OR PhD in a quantitative field and 2+ years professional experience in a data science, machine learning, or related analytical role, Deep understanding of machine learning algorithms, statistical modeling techniques, and their practical applications, Extensive experience using ML frameworks and libraries such as scikit‑learn, TensorFlow, or similar tools, SQL skills, Experience working with large-scale data warehousing platforms, particularly Snowflake, Expert proficiency in a scripting language such as Python, including Python data libraries (numpy, pandas, matplotlib, scikit-learn), Programming skills in Java or similar languages, Intermediate proficiency in a low-level or performant language, Expert proficiency in working within a cloud computing environment using software development best practices, Hands-on experience with cloud platforms (AWS and/or Azure) including services for data storage, processing, and model deployment, Proven track record of deploying machine learning models to production environments and measuring their business impact, Experience automating production-quality statistical or machine learning models at scale with expert understanding of their underlying mathematical and statistical theory, Experience with version control (Git), Experience with containerization (Docker), Experience with CI/CD practices, Experience and expertise solving complex and highly impactful quantitative business problems, Self-starting ability to spearhead new data science initiatives, Collaboration across functional teams, Excellent communication skills with ability to explain statistic and mathematical concepts to non-experts
Nice to Have
PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
and deploy advanced machine learning models and statistical algorithms
Conduct rigorous statistical analysis
and provide actionable insights
Build and optimize end-to-end data pipelines
including data extraction
and feature engineering
and enhance operationalized statistical and machine learning models and algorithms
Create repeatable processes and scalable data products by automating feedback loops for production statistical or machine learning models
Perform exploratory data analysis on large-scale datasets
Implement MLOps best practices
including model versioning and monitoring
Mentor junior data scientists and contribute to the development of team capabilities
Identify areas of opportunity for data science to effect change and drive strategic business impact
Maintain engagement with the data science community and current industry developments
How You'll Work.
Team & Collaboration
work with stakeholders throughout the organization; collaboration across functional teams; Influence functional teams to develop best practices across the organization; knowledge sharing
Communication Scope
excellent communication skills with ability to explain statistic and mathematical concepts to non-experts
Full Job Description
# **Together we make breakthroughs possible.** At OCLC, we build technology with a purpose: to connect libraries and make knowledge accessible worldwide, because we believe that what is known must be shared. Our teams work with complex global datasets, AI and machine learning, hybrid cloud solutions, and other technologies that connect people and organizations to the information they need. We value the power of unique perspectives and experiences to unlock innovation. At OCLC, your ideas matter, whether you have two years of experience or 20. You’ll learn, create, and problem-solve with technologists, product developers, librarians, researchers, marketing pros, and support teams around the world. # **Why join OCLC?** OCLC is consistently recognized as a best place to work by several independent programs. We recognize and reward people and results with a comprehensive Total Rewards package. This means competitive compensation that reflects your unique contributions—performance, experience, and skills—along with exceptional benefits, including best-in-class health coverage, retirement plans with generous company contributions, and a commitment to your overall well-being. * We know the best ideas don’t always happen at a desk. Take a walking meeting around our 100-acre campus or enjoy lunch on the patio. We’re committed to your success—both personally and professionally. Hybrid work environment: For many roles, three days a week on-site, with occasional additional days based on business needs. * Free use of our on-site fitness center, gym sports, group exercise classes, and game room * Onsite catering and cafeteria subsidized by OCLC * Health and wellness events * Work environments with individual and team spaces and the latest technology tools * Paid parental leave and adoption assistance * Tuition reimbursement and Public Service Loan Forgiveness eligibility * Company-subsidized pricing on local tickets and memberships Join us in transforming how people everywhere acc
Applying for this Senior Data Scientist role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about Oclc?
Real rants from real employees. Read before you apply.