Data Scientist

• Develop methods, processes, and systems to consolidate and analyze large qualitative and quantitative datasets (support case data, escalation data, retrospective feedback, telemetry, etc.) to generate trends and actionable insights.
• Perform exploratory data analysis (EDA) to identify patterns, anomalies, and root causes that drive improvement opportunities across CEE operations.
• Design and conduct experiments to test hypotheses, validate assumptions, and measure the impact of business initiatives.

• Apply statistical and machine learning techniques to develop predictive and classification models that solve moderately complex business problems.
• Leverage Natural Language Processing (NLP) and modern ML techniques to extract insights from unstructured text data, including support cases, knowledge base articles, and customer interactions.
• Explore and implement Generative AI and Large Language Model (LLM) based solutions to improve support workflows, content quality, and issue resolution.
• Exposure to AI agents, agentic workflows, and agentic frameworks, with the ability to apply them to real-world business problems
• Train, evaluate, and refine models based on statistical analysis and business feedback, ensuring high model quality and reproducibility.

• Build and maintain automated data pipelines to streamline complex analytical and operational processes across the organization.
• Collaborate with data engineers to optimize data workflows, ensure data quality, and maintain data integrity across systems.
• Work with modern databases, including relational and vector databases, for structured and unstructured data storage and retrieval.

• Develop and maintain interactive dashboards and data visualizations to communicate insights effectively to technical and non-technical stakeholders.
• Translate highly technical findings into clear, actionable business recommendations through written reports, presentations, and storytelling.
• Present key performance metrics and analytical findings to leadership and cross-functional teams.

• Collaborate with cross-functional teams including software engineers, product managers, and program managers to translate business requirements into technical solutions.
• Participate in and contribute to relevant open source communities and tools, aligning with Red Hat's open source culture.
• Proficiently leverage AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude) to optimize code quality and accelerate development cycles.
• Document analytical models, data pipelines, methodologies, and key insights for knowledge sharing and reproducibility.

• Bachelor's degree in Data Science, AI, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
• 3–5 years of professional experience in data science, machine learning, or advanced analytics roles.
• Strong proficiency in Python and its data science ecosystem (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn).
• Solid experience with SQL for data extraction, transformation, and analysis.
• Demonstrated proficiency in statistical analysis, hypothesis testing, regression modeling, and experimental design.
• Experience building and evaluating machine learning models (classification, regression, clustering, NLP).
• Familiarity with NLP techniques and libraries (e.g., spaCy, Hugging Face Transformers, NLTK) for working with text data.
• Experience with data visualization and BI tools such as Tableau, Preset
• Strong communication skills with the ability to explain complex analytical concepts to diverse audiences.
• Demonstrated problem-solving ability coupled with innovative thinking and a customer-centric approach.
• Experience with Generative AI, Large Language Models (LLMs), and prompt engineering.

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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.

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.

Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.