Data Scientist – AI Modelling (3 -5 years only)

About the Role

The FCC DnA team is seeking an experienced Data Scientist to join our AI Modeling team and develop scalable Machine Learning, statistical and AI solutions.

This role is ideal for a hands-on Data Scientist who can independently translate business problems into modeling problems, evaluate multiple analytical approaches and recommend solutions based on data, statistical evidence and business requirements.

You will work across Statistical Modeling, Machine Learning, NLP and Generative AI while partnering with Product, Engineering and Business teams to take solutions from experimentation toward production.

We are looking for someone who goes beyond building a model and can clearly explain why a particular modeling approach was selected, how it was validated and what its limitations are.

Key Responsibilities

· Translate business problems and requirements into appropriate analytical and modeling approaches.

· Independently design, develop and evaluate statistical and Machine Learning models.

· Establish appropriate baseline and challenger models and objectively compare alternative approaches.

· Perform exploratory analysis, feature engineering, feature selection and data-quality assessment.

· Define appropriate model evaluation metrics based on the business problem and the cost of different types of errors.

· Apply cross-validation, hyperparameter tuning, out-of-sample testing and other robust validation techniques.

· Conduct detailed error analysis, sensitivity analysis and model diagnostics.

· Identify and address issues such as data leakage, class imbalance, multicollinearity, sampling bias and overfitting.

· Evaluate model explainability, stability and performance trade-offs.

· Clearly document model methodology, assumptions, limitations and validation results.

· Partner with Engineering and MLOps teams to transition models from experimentation into production.

· Support model monitoring, performance tracking and drift analysis after deployment.

· Build reusable modeling components and frameworks that can be leveraged across multiple use cases.

· Contribute to NLP, Generative AI, RAG and hybrid AI solutions where appropriate.

· Mentor junior Data Scientists and conduct code and model reviews.

· Communicate modeling recommendations and trade-offs effectively to business, Product and technical stakeholders.

Required Qualifications

Experience

· Approximately 3-5 years of hands-on experience in Data Science, Machine Learning, Statistical Modeling or Applied AI.

· Demonstrated experience independently developing and validating predictive models.

· Experience working across the model development lifecycle from data exploration through validation and productionization.

· Experience working with cross-functional Product, Engineering and Business teams.

Statistical & Modeling Skills

· Strong understanding of statistical inference, probability, hypothesis testing and experimental design.

· Strong hands-on experience with regression, classification, tree-based models, ensemble methods and other Machine Learning techniques.

· Experience with algorithms such as logistic/linear regression, random forest, gradient boosting, XGBoost/LightGBM or comparable techniques.

· Strong understanding of feature engineering, feature selection and model diagnostics.

· Experience designing benchmark, baseline and challenger models.

· Strong understanding of model evaluation and the ability to select metrics appropriate to the business problem.

· Understanding of bias-variance trade-offs, sampling bias, class imbalance, data leakage and model stability.

· Experience with explainability techniques such as feature importance, SHAP or similar approaches.

· Ability to assess trade-offs between predictive performance, interpretability, complexity and maintainability.

Technical Skills

· Strong Python and modern Data Science ecosystem experience.

· Strong SQL and data manipulation skills.

· Experience developing production-quality, reusable modeling code.

· Familiarity with APIs and frameworks such as FastAPI.

· Familiarity with Git, Docker, CI/CD, cloud platforms such as Azure/AWS and MLOps practices.

· Experience with model deployment, monitoring and versioning is preferred.

· Experience with NLP, Generative AI, LLMs, embeddings, RAG or Agentic AI is desirable and will enable contribution across broader AI initiatives.

We Are Looking for Individuals Who

· Ask which modeling approach is most appropriate for the problem and can explain why.

· Challenge assumptions rather than automatically selecting the most complex algorithm.

· Are comfortable working with ambiguous business problems and defining a structured analytical approach.

· Balance experimentation with analytical rigor and production considerations.

· Take ownership of modeling workstreams and independently drive them to completion.

· Clearly articulate model performance, assumptions, limitations and business implications.

· Mentor junior team members and raise the quality of modeling practices around them.

· Collaborate effectively with Product, Engineering and business stakeholders.

· Remain current with developments across statistical modeling, Machine Learning and broader Applied AI.

Education

Bachelor's or Master's degree in Statistics, Mathematics, Data Science, Computer Science, Artificial Intelligence, Engineering, Economics or another quantitative discipline.

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.

Be the Difference

If making a difference matters to you, then you matter to us.

Join us, at Wolters Kluwer, and be part of a dynamic global technology company that makes a difference every day.

We’re innovators with impact. We provide expert software and information solutions that the world’s leading professionals rely on, in the moments that matter most. You’ll make a real difference in the lives of millions of people. Together with our customers, we help to advance sustainability, health, justice, prosperity, and commerce around the world.

You can thrive at Wolters Kluwer, where diversity is core to our collective strength and high performance. Be your unique self, share your creative ideas, do your best work, and take time to grow in our caring and inclusive culture where you can belong.

About Wolters Kluwer

Wolters Kluwer reported 2025 annual revenues of €6.1 billion. The group serves customers in over 180 countries, maintains operations in over 40 countries, and employs more than 21,000 people worldwide. ​

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Our customers work in industries that impact the lives of millions of people every single day. Our mission is to empower our professional customers with the AI-powered solutions they need to make critical decisions, achieve successful outcomes, and increase productivity. ​

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We deliver trusted, AI-powered expert solutions that combine deep domain knowledge, proprietary content, and advanced technology to provide expert-validated insights, automate workflows, and drive better outcomes. Today, nearly 70% of our digital revenues come from AI-powered solutions, reflecting our strategic focus on embedding AI into professional workflows and delivering measurable productivity gains. ​

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We are committed to helping professionals navigate complexity, improve the way they work, and solve critical challenges through cloud-based, AI-powered platforms that integrate seamlessly into their workflows and ecosystems. Our solutions are designed to deliver impact when it matters most, especially in high-stakes environments where accuracy and trust are essential. ​

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With a nearly 190-year legacy, Wolters Kluwer continues to evolve its portfolio of digital solutions and services to meet the changing needs of professionals worldwide, enabling them to work faster, make smarter decisions, and deliver better outcomes.​

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For more information about our solutions and organization, visit www.wolterskluwer.com, or follow us on LinkedIn, Instagram and Facebook.

Tips & Tricks - Resumes

Wolters Kluwer has a dedicated team of experienced talent acquisition professionals who are ready to hear what makes you tick and share how Wolters Kluwer can help you achieve your goals and ambitions. Here Rasi Fawaz shares some tips on what recruiters are looking for on a resume.

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As a global organization, we recognize that solving a wide range of complex problems requires diverse perspectives and innovative thinking. We know that bringing our best to our customers, communities, and other key stakeholders requires a highly engaged and talented workforce – one that represents the diversity of those we serve and the communities where we live and work.

We aim to provide a welcoming environment and equitable opportunities for all employees regardless of background, nationality, race, ethnicity, gender, gender identity, age, sexual orientation, marital status, disability, or religion.

This principle is ingrained in our company values and articulated in our Code of Business Ethics.

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At Wolters Kluwer, you’ll feel valued for your contributions, and you’ll know that your health, safety, and well-being are important to us. Our well-being benefits provide tools, programs, and resources to help our diverse employees feel healthy, happy, safe, and prosperous.​

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Our global Together we thrive well-being program reflects our commitment to supporting colleagues across physical, mental, social, and financial well-being. That commitment has been recognized externally through Ragan’s Top Places to Work for Employee Wellbeing: Large Organization in 2024. ​

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More recently, Wolters Kluwer was recognized by Forbes as one of America’s Best Large Employers 2026 and America’s Best Employers for Engineers 2026. In 2025, Wolters Kluwer was also recognized by Forbes as one of America’s Best Employers for Women.

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