About The Role
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. This role is ideal for someone who enjoys both hands-on engineering and deriving insights from data to influence product behavior and decision-making.
Key Responsibilities
Data Science & Advanced Analytics
- 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.
- Ensure data quality, integrity, and consistency across multiple sources.
Software Engineering & System Implementation
- 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.
Data Platforms & Integration
- 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.
Quality, Testing & Responsible AI
- 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.
Collaboration & Mentorship
- 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.
Core Skills & Qualifications
Programming & Engineering
- 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.
Data & Analytics
- 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).
Databases & Platforms
- 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.
Development Practices
- Experience working in Agile environments.
- Strong testing, documentation, and collaboration practices.
- Ability to balance analytical depth with production-quality engineering.
Core Competencies
- Analytical Skills
- Inclusive Collaboration
- Drive to Perform
- Accountability
- Functional Expertise
- Operational Expertise
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.
Compensation:
$102,000.00 - $178,050.00 USD
This role is eligible for Bonus.
Compensation range listed is based on primary location of the position. Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process.
Additional Information:
Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, & Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.
