Business Intelligence Analyst

Role Overview: As a Senior Business Intelligence Analyst in the GBS OpEx & Analytics group at Wolters Kluwer, you will play a crucial role in supporting data-driven projects, conducting routine data analysis tasks, and assisting in model development and testing. Your contributions will be vital in various stages of the data science lifecycle, providing insights to shape business strategies and inform decision-making. This position is ideal for individuals with a foundational understanding of data science who are eager to enhance their expertise. Key Responsibilities: - Conduct root cause analyses to identify and resolve data inconsistencies and performance bottlenecks. - Collaborate extensively across product and business teams to align AI solutions with operational goals. - Integrate Gen AI capabilities (LLMs, SLMs, Agents) using frameworks to enhance automation and decision-making. - Develop, deploy, and maintain robust machine learning models utilizing traditional techniques (e.g., scikit-learn) to support AI-driven operations. - Create insightful visualizations and dashboards to effectively communicate findings and model performance. - Participate in feature engineering and model tuning to enhance accuracy and reliability. - Ensure data integrity and consistency across multiple sources and systems. - Develop and maintain analytical models and reports to support the organization's business operations. - Collaborate with stakeholders to identify data needs and develop solutions. - Utilize data to generate recommendations for process improvements. - Develop and maintain documentation for data models and reports. - Participate in meetings to present findings and recommendations. - Mentor junior team members and cultivate a culture of continuous learning and innovation. Qualifications Required: - Python Expertise: Advanced proficiency in Python for data manipulation, modeling, and automation. - Traditional ML: Strong hands-on experience with scikit-learn and other classical ML libraries. - Gen AI Knowledge: Familiarity with LLMs, SLMs, and agent-based architectures. - Data Engineering: Experience in building and optimizing data pipelines and workflows. - Visualization: Skilled in tools like Matplotlib, Seaborn, Power BI, or Tableau. - Database Proficiency: Strong SQL skills and working knowledge of NoSQL databases. - Communication: Ability to clearly articulate technical concepts to non-technical stakeholders. - Collaboration: Proven ability to coordinate across teams and manage dependencies effectively. - Mentorship: Experience in guiding junior data scientists and contributing to team development. Company Details (if available): Wolters Kluwer is a global leader in professional information services, combining deep domain knowledge with specialized technology. Their portfolio offers software tools, coupled with content and services, that enable customers to make informed decisions with confidence. Every day, their customers make critical decisions to help save lives, improve the way business is conducted, and build better judicial and regulatory systems. Wolters Kluwer strives to assist customers in getting it right. Role Overview: As a Senior Business Intelligence Analyst in the GBS OpEx & Analytics group at Wolters Kluwer, you will play a crucial role in supporting data-driven projects, conducting routine data analysis tasks, and assisting in model development and testing. Your contributions will be vital in various stages of the data science lifecycle, providing insights to shape business strategies and inform decision-making. This position is ideal for individuals with a foundational understanding of data science who are eager to enhance their expertise. Key Responsibilities: - Conduct root cause analyses to identify and resolve data inconsistencies and performance bottlenecks. - Collaborate extensively across product and business teams to align AI solutions with operational goals. - Integrate Gen AI capabilities (LLMs, SLMs, Agents) using frameworks to enhance automation and decision-making. - Develop, deploy, and maintain robust machine learning models utilizing traditional techniques (e.g., scikit-learn) to support AI-driven operations. - Create insightful visualizations and dashboards to effectively communicate findings and model performance. - Participate in feature engineering and model tuning to enhance accuracy and reliability. - Ensure data integrity and consistency across multiple sources and systems. - Develop and maintain analytical models and reports to support the organization's business operations. - Collaborate with stakeholders to identify data needs and develop solutions. - Utilize data to generate recommendations for process improvements. - Develop and maintain documentation for data models and reports. - Participate in meetings to present findings and recommendations. - Mentor junior team members and cultivate a culture of continuous learning and innovation. Qualifications Requi