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.
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.
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.
Benefits
- Medical, Dental, & Vision Plans
- 401(k)
- FSA/HSA
- Commuter Benefits
- Tuition Assistance Plan
- Vacation and Sick Time
- Paid Parental Leave