Senior Data Scientist / Senior Software Engineer

Senior Data Scientist / Senior Software Engineer

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

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