Data Scientist

Business Unit: Legal and Regulatory Division – ELM Solutions

About Us:

At Wolters Kluwer, our Legal and Regulatory division empowers legal and compliance professionals to enhance productivity, mitigate risk, and tackle complex challenges with confidence. Within this division, ELM Solutions offers a comprehensive suite of tools designed to improve the operational efficiency of corporate legal and insurance claims departments. Our innovative technology and customer-focused approach help drive world-class business outcomes for our clients.

About the Role:

We’re seeking a Data Scientist with 3-6 years of experience to join our dynamic team. In this role, you’ll work on AI model development, data analysis, and deployment processes that support our cutting-edge legal solutions. This position offers the opportunity to contribute to meaningful projects that optimize business performance, improve operational efficiency, and drive innovation.

Key Responsibilities:

• AI Model Management: Oversee the configuration, maintenance, and support of AI models, ensuring optimal performance through iterative re-training and enhancements.
• Deployment & Release: Collaborate on AI model releases and ensure smooth production deployments and new client onboarding by configuring model pipelines.
• Cross-functional Collaboration: Work closely with cross-functional teams for seamless integration and deployment of AI solutions.
• Data Analysis & Insights: Conduct data analysis to generate actionable insights, supporting senior data scientists and decision-making.
• Documentation & Continuous Learning: Manage databases, maintain up-to-date documentation, and stay informed about the latest advancements in AI and machine learning tools.

Required Skills:

• Hands-on experience with Generative AI, Large Language Models (LLMs), and advanced Retrieval-Augmented Generation (RAG) techniques.
• Python & Data Science Ecosystem: Proficiency in Python, with hands-on experience in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) techniques.
• Machine Learning & NLP Expertise: Expertise in developing machine learning solutions and a strong background in Natural Language Processing (NLP).
• SQL & Solr Framework: Proficient in SQL and the Solr framework, with Python-based implementations.
• Linux & Scripting: Familiarity with Linux environments and shell scripting.
• Statistical & Algorithmic Foundations: Solid knowledge of statistical modeling, data structures, algorithms, operating systems, and databases.
• Collaboration & Innovation: Strong problem-solving skills, collaboration with cross-functional teams, and a passion for emerging technology trends.

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field; a Master’s degree is a plus.
• 3-6 years of experience supporting software products or applications in the AI/ML domain.