Senior Data Scientist / Senior Software Engineer, Wolters Kluwer
$102-178.1k
+ Bonus
Hybrid (8 days/month)
2+ days a week in office
AI-powered solutions for professionals
Job no longer available
AI-powered solutions for professionals
1001+ employees
Job no longer available
$102-178.1k
+ Bonus
Hybrid (8 days/month)
2+ days a week in office
1001+ employees
Company mission
To help customers make critical decisions every day by providing expert solutions tha to combine deep domain knowledge with technology.
Role
Who you are
- This role is ideal for someone who enjoys both hands-on engineering and deriving insights from data to influence product behavior and decision-making
- Strong proficiency in C#/.NET for enterprise software development
- Strong proficiency in Python for data analysis, modeling, and data pipelines
- Familiarity with R, Java, or C++ is a plus
- Solid understanding of software engineering fundamentals and system design
- Advanced data analysis and problem-solving skills
- Hands-on experience with machine learning algorithms and predictive modeling
- Experience applying analytics to influence product or business outcomes
- Expertise in feature engineering, model tuning, and validation
- Proficiency with data visualization tools (e.g., Tableau, Power BI, Matplotlib)
- Strong SQL skills and relational data modeling experience
- Experience working with cloud platforms, preferably Microsoft Azure
- Familiarity with NoSQL or large-scale data systems is a plus
- Experience working in Agile environments
- Strong testing, documentation, and collaboration practices
- Ability to balance analytical depth with production-quality engineering
- Analytical Skills
- Inclusive Collaboration
- Drive to Perform
- Accountability
- Functional Expertise
- Operational Expertise
What the job involves
- This role blends advanced data science with senior-level software engineering to deliver intelligent, data-driven software solutions
- As a Senior Data Scientist / Senior Software Engineer, you will design and build production-grade systems while applying statistical modeling, machine learning, and analytics to solve complex business problems
- You’ll work across Python-based data science workflows and C#/.NET-based enterprise systems on Azure, partnering closely with product, engineering, and business stakeholders
- Design and execute experiments and A/B tests to evaluate product and business hypotheses
- Develop, validate, and tune machine learning and predictive models
- Perform exploratory and root cause analysis to uncover trends, anomalies, and key drivers
- Lead feature engineering efforts to improve model performance and interpretability
- Apply statistical and mathematical techniques to real-world, applied problems
- Build clear and effective visualizations and analytical summaries for stakeholders
- You'll ensure data quality, integrity, and consistency across multiple sources
- Design and implement services and applications that integrate data science outputs into production systems
- Build and maintain C#/.NET (ASP.NET Core) APIs and backend components on Microsoft Azure
- Develop data pipelines and processing logic supporting analytical and operational use cases
- Collaborate with frontend engineers to enable data-driven experiences
- Optimize application and data pipeline performance, reliability, and scalability
- Prepare, preprocess, and optimize data for analysis and modeling using Python
- Design and query SQL Server / Azure SQL databases for analytical and transactional workloads
- Ensure efficient interaction between analytical models and software systems
- Support model deployment, monitoring, and validation in production environments
- Contribute to testing strategies for data pipelines, models, and software components
- Participate in peer reviews of code, models, and analytical approaches
- Evaluate AI and data tooling thoughtfully and responsibly
- Apply validation and governance practices to AI-assisted code and model outputs
- Communicate analytical findings and technical solutions clearly to technical and non-technical audiences
- Collaborate closely with product, engineering, and business partners
- Mentor junior data scientists and engineers through knowledge sharing and feedback
- Participate in Agile planning, estimation, and delivery activities
Application process
- 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
Our take
For over 185 years, Wolters Kluwer has been innovating the way professionals and businesses work. The company has expanded to offer a substantial range of services across the Health, Tax & Accounting, Finance, Compliance, and Legal sectors.
While operating across so many sectors comes with an extensive range of competition, Wolters Kluwer serves customers in over 180 countries, which has been managed, in part, due to its 70+ acquisitions. For example, the company has recently acquired leading artificial intelligence technology company Della AI, which will become part of its legal software unit, to further advance its natural language processing capabilities.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Company HQ
Alphen aan den Rijn, Netherlands
Leadership
Nancy McKinstry
(CEO & Chairman of the Executive Board, not founder)Held various roles at the company before being named CEO in 2003. Current Member of the Board of Directors at various companies including Accenture, Abbot, Russel Reynolds Associates, and Columbia Business School.
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