Senior Data Scientist

Leverage advanced data analysis, statistical, and machine learning techniques to analyze large datasets (big data) from test results and logs, identifying patterns and trends to develop and implement data-driven solutions that align with strategic business objectives.
* Telecommuting permitted: work may be performed within normal commuting distance from the Red Hat, Inc. office in Boston, MA.
What You Will Do:

• Develop and code software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from disparate sources.
• Develop and deploy machine learning and natural language processing (NLP) models on Open Shift and Open Shift AI, enhancing the productivity and efficiency of the Quality Engineering (QE) teams at Red Hat.
• Take ownership of MLOps responsibilities for both new and existing AI/ML applications, managing the end-to-end model lifecycle, including training, versioning, deployment, monitoring, and continuous improvement to ensure model reliability and scalability.
• Implement and optimize NLP embedding and inference models on Open Shift AI to deliver robust natural language understanding capabilities, leveraging cutting‑edge techniques to enhance model performance and application effectiveness.
• Apply prompt optimization techniques such as few‑shot learning, chain‑of‑thought prompting, and other advanced methods to improve model outputs and facilitate efficient model performance across various use cases.
• Implement RAG (Retrieval‑Augmented Generation) and model tuning using Instruct Lab and RHEL AI, fine‑tuning large language models for context‑specific applications that improve responsiveness and deliver tailored insights to users.
• Design strategic roadmaps and develop, test, and maintain Python scripts to deploy machine learning models and data pipelines into production environments, ensuring high‑quality standards and seamless integration with existing infrastructure.
• Analyze data to identify trends, anomalies, and key insights, documenting findings to support further investigation, continuous feedback loops, and improvements in model accuracy and application efficacy.
• Participate in the end‑to‑end AI/ML project lifecycle, including requirements gathering, workflow design, scheduling, and milestone setting to ensure projects meet delivery timelines and align with Red Hat’s strategic goals.
• Strategize and oversee the AI/ML project lifecycle, ensuring comprehensive project execution in line with scope and timelines, and adjusting strategies based on feedback and evolving needs.
• Collaborate cross‑functionally with the data science and QE teams to enhance data analytics, improve model functionality, and streamline development processes.
• Keep up with AI/ML developments and research papers, particularly in the Generative AI space.
• Access and maintain comprehensive databases of test results and log files from QE teams, ensuring that data pipelines remain accurate, secure, and accessible for analysis and model training.
• Monitor and visualize key metrics and defect logs using tools like Tableau, Splunk, Grafana and Kibana, creating intuitive dashboards and providing technical support to internal teams and customers to drive data‑informed decision‑making.
• Participate in an agile development team and experience working within an open‑source community.
• Lead, coach and collaborate with junior engineers as they build AI/ML knowledge and skills.

What You Will Bring:

• Bachelor’s degree (U.S. or foreign equivalent) in Computer Science, Information Systems, Mathematics or related field and five (5) years of experience in the job offered or related role OR Master’s degree (U.S. or foreign equivalent) in Computer Science, Information Systems, Mathematics or related field and three (3) years of experience in the job offered or related role.
• Must have three (3) years of experience with:
  Python scripting language; SQL; statistical data analysis and visualization methodologies; classical machine learning modeling; natural language processing (NLP) models; and Docker, Airflow, CI/CD.
• Must have two (2) years of experience with: model deployment and MLops methodologies; and Openshift.
• Must have…