Red Hat’s Global Sales Go-To-Market (GTM) team is looking for a high-impact Principal Data Scientist to bridge the gap between complex data architecture and executive strategy. This isn’t a "maintenance" role—you will be an architect of change, leveraging AI, advanced statistics, and a builder’s mindset to reinvent how we handle quotas, incentives, and sales capacity. We need a hybrid talent: someone with the technical depth to code automated pipelines from scratch and the business savvy to translate those results into a "digestible story" for executive leadership. What You Will Do - Architect from Scratch: Design and deploy end-to-end automated processes for the quota and incentive lifecycle, ensuring bulletproof data validation - Scale AI Integration: Use advanced prompt engineering and LLM tools to accelerate development, audit code, and eliminate manual workflows - Master the Pipeline: Extract and enrich massive datasets from Snowflake and GitHub, ensuring data integrity across complex logic layers - Tell the Story: Translate highly technical outputs into strategic recommendations. You will present key performance metrics directly to executive leadership - Solve the "Puzzle": Apply predictive modeling and pattern recognition to evaluate sales coverage and optimize customer engagement at scale What You Will Bring - Programming: Mastery of Python (Pandas, Google Cloud libraries) and SQL (Snowflake/DBeaver) - AI Fluency: You treat AI as a primary collaborator, using prompt engineering to increase your velocity - Statistics: Deep knowledge of regression, simulation, scenario analysis, clustering, and decision trees - Data Ops: Experience with GitHub workflows and building "self-healing" scripts to prevent recurring data errors - Visualization: Ability to build impactful narratives in Tableau, Google Sheets, and Salesforce CRMA - Experience: 10+ years of professional experience manipulating large datasets and building production-grade statistical models - The Mindset: You thrive in "barely tested" environments and high-pressure situations where the logic hasn't been defined yet - Business Acumen: A background in Sales Operations, Finance, or GTM strategy within the tech industry is highly preferred - Process Engineering: You don’t just find errors; you build the automation to ensure they never happen again - Education: Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related quantitative field Why Join Red Hat? You won't be a cog in a machine. You will be reinventing the machine itself. We offer a high-visibility environment where your work has a direct, measurable impact on Red Hat’s global revenue. If you are naturally curious and love solving puzzles with real-world financial stakes, this is your next move. Are you ready to build the future of sales intelligence? The salary range for this position is $123,130.00 - $203,100.00. 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. 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. 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.

As an AI-Native Data Scientist at ConsumerAffairs, you will design and build AI-driven solutions that help us better understand consumers, improve marketplace performance, and accelerate business growth. You will partner closely with engineering, product, and business leaders to develop predictive models, generative AI applications, and data products—such as consumer sentiment models—that directly influence decision-making across the company. This is a hands-on, outcome-oriented role. You will work across the full lifecycle of AI and data science solutions—from identifying high-impact business opportunities and designing experiments to building models, deploying them into production, and iterating based on real-world performance. You will operate in a modern data environment that includes tools such as AWS, Databricks, Python, and large language model ecosystems. In this role, you will also evaluate and apply emerging AI technologies that increase productivity and unlock new capabilities. We are looking for someone who is both analytically rigorous and AI-native in mindset—someone who actively uses modern AI tools, embraces experimentation, and enjoys turning complex data into scalable, intelligent systems. Responsibilities include: - Partner with business and technical teams to identify opportunities where machine learning, predictive modeling, or generative AI can create measurable business impact. - Design, build, and deploy machine learning and AI solutions, including predictive models, recommendation systems, and LLM-powered applications that improve customer understanding and decision-making. - Develop scalable data pipelines and feature engineering workflows using tools such as Python, SQL, and cloud-based data platforms to support analytics and model development. - Apply modern machine learning techniques, including supervised and unsupervised learning, experimentation frameworks, and large language models (LLMs), to extract insights and automate complex tasks. - Own the model lifecycle, including training, evaluation, monitoring, and iteration, ensuring models remain reliable and impactful in production environments. - Contribute to ML operations workflows, including infrastructure configuration, API development for model access, and deploying models into batch or real-time production systems. - Leverage modern AI platforms and tools (e.g., OpenAI, Anthropic, vector databases, managed cloud ML services) to accelerate experimentation and product development. - Communicate insights and model results clearly through dashboards, visualizations, and presentations that translate technical findings into actionable recommendations. - Continuously evaluate new AI tools, frameworks, and methodologies to improve team productivity and unlock new capabilities for ConsumerAffairs.

• Manage a team in building interactive dashboards, predictive models, and reporting solutions using tools such as Power BI, Python, SQL • Lead by example while managing and developing the Analyst team—providing hands-on guidance, mentorship, and fostering professional growth through direct involvement in project work. • Delivery of analysis, dashboards, and sharp insights that enable functional leaders to quickly understand and effectively make decisions to manage the global performance of complex solution and service offerings • Apply advanced analytics techniques (statistical modeling, machine learning) to identify trends, forecast outcomes, and support business decision making • Guide automation of data processing and transformation using Python, SQL, and modern cloud-based platforms • Establish and enforce data governance and quality assurance standards across all projects. • Mentor and coach junior staff, promoting professional growth and innovative problem-solving

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role provides an exciting opportunity to lead a global data science organization, shaping the next generation of data-driven solutions in a fast-paced, high-impact environment. The Sr Director, Data Science will oversee teams responsible for advanced modeling, AI, and predictive analytics that inform business decisions and improve outcomes. You will partner closely with product, engineering, and commercial leaders to implement scalable, compliant, and innovative data initiatives. This position involves leading distributed teams across multiple geographies, fostering a culture of experimentation and collaboration, and driving strategic projects that leverage healthcare or similar domain-specific data. The role emphasizes ethical, privacy-aware data practices while delivering measurable business impact. - Lead and mentor a global team of data scientists, fostering innovation, collaboration, and technical excellence. - Develop and oversee predictive, causal, and machine learning models to drive actionable insights and business impact. - Partner with product, engineering, and commercial teams to implement scalable data solutions aligned with organizational priorities. - Ensure data science practices comply with relevant privacy, regulatory, and ethical standards. - Contribute to the strategic planning of data initiatives, identifying opportunities for advanced analytics and AI integration. - Strengthen data infrastructure, feature engineering, reproducibility, and ML Ops processes to improve reliability and scalability. - Translate complex modeling outputs into clear insights for stakeholders and clients. Qualifications - Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field; Master’s or Ph.D. preferred. - 8+ years of experience in data science, machine learning, or advanced analytics roles. - 5+ years of experience managing and mentoring data science or analytics teams. - Experience with healthcare data, adtech, marketing analytics, or other domain-specific large-scale datasets. - Strong expertise in Python, SQL, Spark, and modern ML frameworks (TensorFlow, PyTorch, XGBoost). - Deep understanding of statistics, causal inference, and media measurement or attribution methodologies. - Experience with privacy-aware data practices and regulatory frameworks (HIPAA, GDPR, CCPA). - Excellent communicator with the ability to convey technical concepts to business stakeholders. - Comfortable operating in global, cross-functional teams across multiple time zones. Benefits - Competitive base salary with performance-based bonus potential. - Comprehensive medical, dental, and vision coverage. - 401(k) with employer match. - Flexible remote or hybrid work options depending on location. - Unlimited PTO, paid holidays, and parental leave. - Professional development, education support, and career growth opportunities. - Additional perks such as home internet stipend, wellness programs, and flexible work arrangements. Company Description