Data Science Intern

​Why Ryan?

Ryan LLC is seeking an intern from the Rotman School of Management to join our Property Tax Data Science team. In this role, you will leverage your analytical expertise to translate complex data into actionable insights that drive tax strategies and business decisions for our UK clients. You’ll partner with cross-functional teams—tax professionals, technology, and external stakeholders—to gather requirements, ensure data integrity, and deliver a practicum project that power Ryan’s industry-leading tax solutions.

Key Responsibilities & Accountabilities

Data Management & Analysis

• Extract, clean, transform, and validate large internal and external data sets (e.g., ERP exports, tax filings, market data) using SQL, Python, R or similar tools.
• Develop and maintain automated data pipelines and ETL processes to feed Advanced Analytics and reporting platforms.
• Validate data integrity, troubleshoot anomalies, and implement data-quality controls.
• Collaborate with Data Scientists to design, develop, and validate predictive and prescriptive models (e.g., classification, regression, clustering) using Python, R, or similar tools.

Insights & Reporting

• Design, build, and maintain interactive dashboards and visualizations (Tableau, Power BI) that communicate key tax metrics and trends to tax practitioners and clients.
• Perform ad-hoc analyses to answer business questions—e.g., opportunity identification, savings forecasts, compliance gaps—and translate findings into clear, actionable recommendations.
• Partner with Business Managers to prioritize reporting needs across Ryan needs.

Collaboration & Stakeholder Engagement

• Work closely with tax subject-matter experts, IT teams, and external vendors to understand requirements, align on data definitions, and deliver timely solutions.
• Present analytical findings to both technical and non-technical audiences, tailoring communication to drive adoption and informed decision-making.
• Participate in Agile ceremonies (sprint planning, stand-ups, retrospectives) to ensure continuous delivery and iterative improvement.

Governance & Best Practices

• Document data models, pipeline architectures, and analytical methodologies to ensure reproducibility and knowledge transfer.
• Adhere to Ryan’s information security policies, data-privacy regulations, and best practices for data governance.
• Stay current on analytics and BI trends (e.g., machine learning, data visualization techniques) and share learnings with the team.

Qualifications & Requirements

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or related field.
• 1-2 years of professional experience in data analysis, business intelligence, or a related analytics role.
• Proven ability to write complex SQL/Hive queries against large relational databases.
• Proficiency in one or more programming languages (Python, R) for data manipulation and analysis.
• Experience developing dashboards and reports in Tableau, Power BI, or similar BI tools.
• Strong understanding of data warehousing concepts and ETL best practices.
• Excellent communication skills, with the ability to translate technical analyses into clear business insights.
• High attention to detail, strong problem-solving skills, and a results-oriented mindset.
• Proficiency with Microsoft Excel and PowerPoint.

Preferred Qualifications

• Experience in the professional services or tax services industry.
• Familiarity with cloud-based data platforms (AWS, Azure) and big-data frameworks (Spark, Hadoop).
• Exposure to machine learning/deep learning modeling techniques and tools.
• Hands-on experience with version control (Git) and Agile development processes.
• Certifications in analytics or data visualization (e.g., Tableau Desktop Certified) or relevant data engineering credentials.
• Ability to mentor junior analysts and foster a collaborative, inclusive team culture.

Compensation Summary: For Ontario based positions, this role pays $19/hr. The firm makes offers based on many factors, including qualifications and experience.