Senior Data Scientist

Cloudera empowers people to transform complex data into clear and actionable insights. We are seeking a talented and curious Senior Data Scientist to join our fast-paced, data-driven organization. In this role, you will design and deliver AI-powered systems and applications that accelerate decision-making and enhance operational excellence. You will combine strong statistical foundations, advanced programming expertise, and modern Generative AI techniques to build scalable, production-ready solutions. This is a builder-focused role. You will move beyond analysis to develop internal copilots, AI-enabled workflows, and reusable platform components that embed intelligence directly into business processes.

Responsibilities

Design, develop, and deploy GenAI-powered internal applications, copilots, and workflow accelerators; Build reusable AI components, including retrieval pipelines, structured prompting patterns, orchestration workflows, and evaluation harnesses; Design retrieval strategies that connect LLMs to trusted internal knowledge sources, ensuring grounded and reliable outputs; Develop and maintain statistical and machine learning models to support automation, optimization, forecasting, and classification use cases; Implement evaluation and validation frameworks to measure quality, accuracy, and consistency of AI-driven systems; Partner cross-functionally to identify high-value opportunities for AI enablement across the organization; Create reusable datasets, feature pipelines, and experimentation frameworks to support iterative development; Uphold high standards for quality, reliability, and responsible AI practices; Contribute to peer review processes to ensure technical rigor and maintainability; Document methodologies, assumptions, and implementation details to ensure transparency and reproducibility

Requirements

Generative AI & LLM Engineering: Hands-on experience working with large language models (LLMs) and modern AI tooling, including prompt design, structured output generation, retrieval-augmented generation (RAG), evaluation strategies, and workflow automation; Ability to translate GenAI capabilities into reliable, enterprise-ready solutions that integrate with existing systems and data sources; AI Application Development Experience: rapidly prototyping and iterating on internal applications, copilots, or AI-enabled workflow tools; Comfortable evolving prototypes into maintainable, production-grade solutions; Platform-Oriented Thinking: Demonstrated ability to design reusable components such as shared prompt libraries, retrieval pipelines, evaluation frameworks, and standardized integration patterns that enable scalable AI adoption; Data Science & Machine Learning Expertise: Proficiency in Python (or R) for data preparation, feature engineering, statistical modeling, and machine learning; Experience with core data science libraries (e.g., Pandas, NumPy, scikit-learn) and a solid understanding of supervised and unsupervised learning methods; Strong Mathematical and Statistical Foundation: Deep understanding of probability, statistical inference, experimentation, and quantitative reasoning to ensure model robustness and reliability; SQL & Data Fluency: Strong understanding of relational databases and the ability to quickly learn new schemas and data environments; Comfortable writing efficient, production-grade SQL to support modeling, experimentation, and AI-enabled applications; Exceptional Communication Skills: Ability to translate complex business challenges into technical solutions and clearly communicate findings, trade-offs, and recommendations to both technical and non-technical stakeholders; Collaborative Development Experience: Experience working in collaborative environments such as Cloudera Data Science Workbench, Jupyter, Zeppelin, or similar platforms; GitHub Proficiency: Experience using version control to support collaboration, code review, documentation, and long-term maintainability; Hands-on experience building applications or workflows powered by large language models (LLMs); Evidence of a builder mindset through shipped AI tools, internal platforms, or automation solutions; Demonstrated experience applying machine learning techniques in production or enterprise environments; 5+ years of relevant experience in Data Science, Machine Learning, or AI-focused roles; Strong curiosity for emerging AI technologies and the ability to evaluate and adopt them responsibly; Academic background in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field

Nice to have

Familiarity with modern development frameworks (e.g., Streamlit, Gradio, FastAPI, or similar) is beneficial; Experience with vector databases, embedding models, or semantic retrieval systems; Experience designing internal AI platforms or shared enablement frameworks; Familiarity with API-driven architectures and integrating AI capabilities into enterprise systems; Exposure to responsible AI practices, governance frameworks, or model lifecycle management

Benefits

Generous PTO Policy; Support work life balance with Unplugged Days; Flexible WFH Policy; Mental & Physical Wellness programs; Phone and Internet Reimbursement program; Access to Continued Career Development; Comprehensive Benefits and Competitive Packages; Paid Volunteer Time; Employee Resource Groups