Sr Technician, Data Analysis

• Support the development, testing, and deployment of analytical and Machine Learning (ML) solutions that help address complex business problems. 

• Analyze large, structured datasets to identify trends, patterns, and actionable insights that support business decisions. 

• Prepare and transform data, perform feature engineering, and assist with model validation activities. 

• Create reports, data visualizations, and presentations that communicate analytical findings clearly to technical and business audiences. 

• Collaborate with Data Science and Analytics team members on research initiatives and data-driven projects. 

• Partner with cross-functional colleagues to clarify analytical needs and contribute to appropriate data solutions. 

• Document analytical methods, assumptions, findings, and project outcomes to support knowledge sharing and repeatable processes. 

• Currently enrolled in the final two years of a bachelor’s degree program, or recently graduated, in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related discipline. 

• Candidates from other academic disciplines who have completed relevant Data Science coursework are encouraged to apply. 

• No professional Data Science experience is required. 

• Demonstrated interest in data, analytics, problem-solving, and the practical application of analytical methods. 

• Strong analytical thinking, critical reasoning, intellectual curiosity, and verbal and written communication skills in English. 

Required Technical Skills 

• Foundational programming knowledge in Python or R. 

• Basic understanding of Structured Query Language (SQL) and relational databases. 

• Foundational understanding of statistics, probability, and data analysis concepts. 

• Exposure to Machine Learning (ML) concepts through coursework, academic research, or projects. 

• Ability to work with structured datasets and derive meaningful insights. 

We’re also looking for the preferred skills below. Whether you are proficient or could use some brushing up, we’re happy to support your career development and growth in: 

• Experience as a Teaching Assistant, Research Assistant, tutor, or student mentor. 

• Participation in university research, academic publications, or conference presentations. 

• Completion of academic, personal, or capstone projects involving data analysis or Machine Learning. 

• Participation in Data Science competitions or hackathons. 

• Experience collaborating on multidisciplinary academic or project teams.

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