Business Intelligence Analyst

About Wolters Kluwer:
Wolters Kluwer is a global leader in professional information services, combining deep domain knowledge with specialized technology. Our portfolio offers software tools, coupled with content and services, that enable customers to make informed decisions with confidence. Every day, our customers make critical decisions to help save lives, improve the way we do business, and build better judicial and regulatory systems. We help them get it right.
Who We Are: Wolters Kluwer - The world is a big place find your place here.
About GBS Analytics:
The GBS Analytics group focuses on analyzing raw data to answer questions, identify trends, and develop insights. The team utilizes various tools and techniques to establish better data standards, consolidate data, and implement governance through visual dashboards that enhance visibility and increase transparency. To date, the team has partnered with various stakeholders to solve business problems, enabling changes at Wolters Kluwer that optimize data assets, inform decision-making, enhance efficiency, and drive savings.
About the Role:
As a Sr. Business Intelligence Analyst in the GBS OpEx & Analytics group, you'll play a crucial role in supporting data-driven projects, performing routine data analysis tasks, and assisting with model development and testing. Your role involves contributing to various stages of the data science lifecycle and providing insights that help shape business strategies and inform decision-making. This position is suited for those with a foundational understanding of data science and who are eager to deepen their expertise.

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 using traditional techniques (e.g., scikit-learn) to support AI-driven operations.
. Create insightful visualizations and dashboards to communicate findings and model performance.
. Participate in feature engineering and model tuning to improve 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 develop 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 foster a culture of continuous learning and innovation.

Skills:
. 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 building and optimizing data pipelines and workflows.
. Visualization: Skilled in tools like Matplotlib, Seaborn, Power BI, or Tableau.
. Database Proficiency: Strong SQL 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 guiding junior data scientists and contributing to team development.

Education and Experience:
. Bachelor's degree (B.E./ B Tech. computer science, engineering, statistics/mathematics, or a related field) from a four-year college or university, or equivalent, master's a plus.
. Total of at least 4-5 years of experience working in Data Analytics and enterprise AI products
. Experience in supporting software products or applications in the AI ML domain.

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