Senior Data Scientist (AI Operations)(6-9 years exp only)
Summary
Senior Data Scientist leading operational excellence for production AI and GenAI applications—handling enhancements, customer onboarding, release management, and compliance—using Python, LLMs, LangChain, RAG architectures, and SQL.
About the Role:
As a Senior Data Scientist - AI Operations, you will play a critical role in driving the stability, scalability, and continuous improvement of production AI and GenAI applications. You will lead complex operational initiatives across application enhancements, customer onboarding, release management, compliance activities, and stakeholder engagement. This role requires strong technical expertise in modern AI technologies, the ability to manage strategic customer relationships, and the leadership skills to guide operational excellence across a growing portfolio of AI solutions.
Responsibilities:
• Lead enhancement, maintenance, and optimization efforts for existing AI and GenAI applications.
• Drive resolution of complex production issues, root cause investigations, and performance improvements.
• Lead customer onboarding activities and ensure successful adoption of AI solutions for new clients.
• Design, develop, validate, and enhance machine learning and GenAI-based solutions.
• Oversee release planning, deployment activities, production readiness reviews, and post-release support.
• Support AI governance, audit, security, risk, and compliance initiatives.
• Partner with product, engineering, and business stakeholders to define priorities and deliver customer-focused solutions.
• Manage customer communications, set expectations, and provide technical guidance during critical initiatives.
• Identify opportunities for automation, operational efficiency, and process improvements.
• Mentor junior team members and provide leadership across AI Operations initiatives.
• Evaluate and adopt emerging AI technologies, frameworks, and best practices to improve platform capabilities.
Skills:
• Generative AI Expertise: Strong understanding of LLMs, LangChain, LangGraph, Agentic AI, RAG architectures, orchestration frameworks, and AI solution lifecycle management.
• Machine Learning: Proven experience developing, evaluating, deploying, and supporting ML solutions in production environments.
• Python: Advanced proficiency in Python for AI/ML development, automation, and operational support.
• Data Analysis & SQL: Strong analytical and troubleshooting skills with complex data environments.
• AI Operations: Experience managing production AI applications, release processes, monitoring, and operational excellence initiatives.
• Compliance & Governance: Understanding of AI governance, security, privacy, risk management, and regulatory requirements.
• Stakeholder Management: Proven ability to manage customer relationships, align expectations, and influence outcomes across multiple teams.
• Communication & Leadership: Strong written and verbal communication skills with the ability to explain complex technical concepts and mentor team members.
Our Interview Practices
To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.
Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.