Senior Data Scientist
OCLC —Dublin, OH
- Full-time
- Hybrid work
- Azure
- Computer Science
- Office
- Paid parental leave
- Health insurance
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Senior Data Scientist
OCLC —Dublin, OH
Master’s Degree in a quantitative field (Mathematics, Computer Science, or Statistics or related quantitative fields) and 5+ years professional experience in a…
Software Engineer II- Full-stack Developer
Deloitte —Columbus, OH
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise.
$95,600 - $188,400 a year

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Senior Data Scientist

OCLC -
Dublin, OH

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Job Details

Full-time

Benefits

Paid parental leave
Health insurance
On-site gym
Tuition reimbursement
Adoption assistance
Parental leave
Loan forgiveness
Retirement plan

Qualifications

AI models
Containerization systems
Version control
Commercial use (data warehousing systems)
Software engineering
Predictive modeling analysis
Continuous Delivery (CD) implementation
Cloud data warehouses
Software deployment
Git
AI platforms (beyond public GPTs)
Computational framework
Snowflake
Programming languages
Machine learning cloud services
Machine intelligence
Model deployment
Scalability
Model training
DevOps automation
Machine learning libraries
Cross-functional collaboration
Machine learning frameworks
Data analysis software
Database software proficiency

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 access information and be part of a mission-driven team that makes a global impact.

The job details are as follows:

As a Senior Data Scientist you will work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions

Responsibilities:

Design, develop, and deploy advanced machine learning models and statistical algorithms to solve complex business problems and drive data-driven decision making across the organization
Conduct rigorous statistical analysis, validate hypotheses, and provide actionable insights to stakeholders
Build and optimize end-to-end data pipelines, including data extraction, transformation, and feature engineering to support scalable ML solutions
Review, scale, and enhance operationalized statistical and machine learning models and algorithms, and quantify improvements in terms of business efficiency or customer experience
Create repeatable processes and scalable data products by, for example, automating feedback loops for production statistical or machine learning models
Perform exploratory data analysis on large-scale datasets to uncover patterns, trends, and opportunities for innovation
Implement MLOps best practices, including model versioning and monitoring to ensure reliable model performance in production.
Mentor junior data scientists and contribute to the development of team capabilities through code reviews, knowledge sharing, and best practice documentation
Influence functional teams to develop best practices across the organization
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 to assist in driving technical data science team vision and strategy

Requirements:

Master’s Degree in a quantitative field (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, along with extensive experience using ML frameworks and libraries such as scikit‑learn, TensorFlow, or similar tools.
Strong SQL skills and 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) and strong 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), containerization (Docker), and CI/CD practices
Experience and expertise solving complex and highly impactful quantitative business problems
Self-starting attitude; ability to spearhead new data science initiatives and collaboration across functional teams
Demonstrates excellent communication skills with ability to explain statistic and mathematical concepts to non-experts

Working Conditions: Normal office environment.

ADA/EAA: The above statements cover what are generally believed to be principal and essential functions of this job. Specific circumstances may allow or require some people assigned to the job to perform a somewhat different combination of duties.

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