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Senior Data Scientist — Applied Analytics (Data & AI)

Red Hat

Raleigh, USonsite$119k-$196k/yrPosted Jun 2, 2026

Skills

kubernetesregressionclusteringsnowflakecomposepandasgithubpythondbtllm

About the role

Red Hat will not be providing visa sponsorship for this position. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.

About the Job

The Senior Data Scientist on Applied Analytics drives data-driven decision-making and shapes approaches across high-priority data projects. Sitting at the intersection of our enterprise data platform and first-party datasets, this role resolves complex data issues and manages the data pipelines that power renewals, lifecycle, and sales activation. Seniors exercise good judgment on data modeling and quality, working with minimal instruction to transition from reactive reporting to proactive insights that integrate directly into the business workflow.

Note: This role may come into contact with confidential or sensitive customer or sales information requiring treatment in accordance with Red Hat policies and applicable privacy laws.

What You Will Do

Lead Strategic Programs: Drive end-to-end data initiatives from problem framing and experimental design to delivery, including proof-of-concepts, stakeholder validation, and handoff to production-style patterns (orchestrated pipelines, dbt models, and production-grade data products).

Architect Decision Logic: Refine the datasets and logic supporting strategic motions, such as funnel engagement behavior, cross-sell/risk signals, and adoption analytics for high-visibility sales programs.

Deep Cross-Functional Partnership: Collaborate across Data & AI and the business (Product, GTM, Marketing and Sales) to resolve ambiguity and align on trade-offs regarding scope, quality, and compliance.

Advance Responsible AI & Methodology: Apply LLM-assisted methods to accelerate synthesis and code development while owning the validation, reproducibility, and human-in-the-loop review for all outputs affecting business, customer and partner stakeholders.

Communicate with Impact: Translate advanced technical work and novel methodologies into clear, jargon-free recommendations for senior leadership to facilitate data-driven decision-making.

Elevate Technical Standards: Mentor analysts and data scientists on analysis design, statistical rigor, and stakeholder management; guide the team through enterprise platform norms such as masking and data-product operationalization.

What You Will Bring

Technical Skills & Tooling

Programming Proficiency: Strong mastery of Python (specifically Pandas and enterprise cloud libraries) and expert-level SQL (Snowflake/DBeaver environments).

AI Fluency: Comfort treating AI as a primary development collaborator, using prompt engineering and modern IDEs to increase coding velocity and automate manual tasks.

Data Ops & Automation: Solid experience with GitHub workflows and a process-engineering mindset—you enjoy building automated data validation scripts to proactively catch and prevent recurring data issues.

Statistics & Modeling: Solid practical knowledge of regression, simulation, scenario analysis, clustering, and decision trees applied to real-world business problems.

Visualization: Ability to build clear, scannable data narratives across various mediums (slide decks, dashboards, and reporting frameworks) using at least one major enterprise BI platform.

Experience & Domain Expertise

Professional Experience: 5–8+ years of professional experience manipulating large datasets, building analytical pipelines, and deploying statistical or predictive models.

Business Acumen: Experience operating within tech/SaaS business models—ideally supporting Sales Operations, Finance, GTM strategy, or lifecycle analytics—is highly preferred.

Education: Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related quantitative field.

The Mindset

You are comfortable dealing with ambiguity and can navigate fast-paced environments where the business logic hasn't been fully defined yet, using pattern recognition to structure and execute solutions.

Success Looks Like:

Driving Behavioral Change: Delivering highly credible, repeatable data applications and prescriptive insights that directly influence business decisions.

Data Integrity: Building and maintaining clean, documented, and rigorous metric definitions within your project domains.

Consistent Delivery: Ensuring predictable project execution through early identification of technical blockers and scope constraints.

Collaborative Growth: Strengthening the team’s overall output through active participation in code reviews, technical documentation, and shared engineering standards.

#LI-HM1

The salary range for this position is $118,600.00 - $195,680.00. Actual offer will be based on your qualifications.

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat’s compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.

About Red Hat

Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.

Benefits

Comprehensive medical, dental, and vision coverage

Flexible Spending Account - healthcare and dependent care

Health Savings Account - high deductible medical plan

Retirement 401(k) with employer match

Paid time off and holidays

Paid parental leave plans for all new parents

Leave benefits including disability, paid family medical leave, and paid military leave

Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

Note: These benefits are only applicable to full time, permanent associates at Red Hat located in the United States.

Inclusion at Red Hat

Red Hat’s culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.

Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee.

Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email application-assistance@redhat.com. General inquiries, such as those regarding the status of a job application, will not receive a reply.

Compensation

This Data Scientist role pays $119k-$196k/yr. Within typical range for data scientist roles in United States.

Questions about this role

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