Senior Data Scientist / Senior Software Engineer

Wolters Kluwer•Chicago, IL

About The Position

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.

Requirements

Strong proficiency in C#/.NET for enterprise software development.
Strong proficiency in Python for data analysis, modeling, and data pipelines.
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 .
Experience working in Agile environments.
Strong testing, documentation, and collaboration practices.
Ability to balance analytical depth with production-quality engineering.

Nice To Haves

Familiarity with R, Java, or C++ is a plus.
Familiarity with NoSQL or large-scale data systems is a plus.

Responsibilities

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.
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.