Senior Data Scientist - Scientifique des données principal(e) (niveau senior)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist - Scientifique des données principal(e) (niveau senior) based in Canada. This role focuses on transforming large-scale tabular and user-behavior datasets into reliable, production-ready inputs for machine learning systems. You will work at the intersection of data science, product, and engineering, helping teams translate business and technical goals into actionable data requirements. Your expertise will guide how datasets are curated, filtered, structured, validated, and prepared for model training. You will collaborate closely with ML engineers, Product teams, and Technical Program Managers in a fast-paced technology environment. The role combines hands-on technical work with cross-functional leadership and strong attention to data quality. Your contributions will help enable robust, scalable machine learning solutions and improve the quality of data-driven products.

You will serve as a technical bridge between data science, machine learning, product, and engineering teams, ensuring that data requirements are clearly defined and that datasets meet the standards required for production-level machine learning. Collaborate with ML engineers, Product teams, and Technical Program Managers to define data and model training requirements. Develop and oversee data strategies for curating, filtering, processing, and preparing large tabular and behavioral datasets. Translate high-level product and machine learning objectives into clear, actionable data specifications for engineering and annotation teams. Ensure datasets are structured and aligned with product objectives and machine learning requirements. Analyze behavioral data to assess its accuracy, representativeness, completeness, and suitability for model training. Maintain high standards of data integrity and quality throughout the data preparation lifecycle. Partner with cross-functional teams to identify data gaps, inconsistencies, and opportunities for improvement. Help establish scalable processes and requirements for production machine learning datasets. Communicate technical data requirements effectively across different engineering and product disciplines. Contribute to data science practices, experimentation, and analytical approaches that support evolving product and ML initiatives. Requirements: The ideal candidate combines strong data science fundamentals with hands-on experience working with large datasets and the ability to collaborate effectively across multidisciplinary technical teams. Bachelor’s or Master’s degree, or relevant certification, in Data Science, Computer Science, Computational Sciences, or a related field. 3+ years of relevant industry experience as a Data Scientist, ideally within a fast-paced, high-growth technology environment. Proven experience working with large tabular and user-behavior datasets. Experience translating product or machine learning objectives into concrete data requirements and specifications. Strong understanding of data science fundamentals, statistics, and mathematics. Fluency in Python, Git, and Unix shell environments. Familiarity with collaborative and engineering tools such as Jira, Confluence, Slack, Git-based workflows, and experiment tracking frameworks. Experience with data visualization and inspection tools designed for analyzing user behavior is an asset. Experience working in complex, multidisciplinary environments such as robotics, streaming services, game development, search engines, or e-commerce is highly valued. Strong analytical and problem-solving skills with exceptional attention to detail. Demonstrated commitment to data accuracy, integrity, and quality. Excellent communication and collaboration skills, with the ability to work effectively across engineering, product, ML, and technical program teams. Ability to operate effectively in a fast-paced environment while managing evolving priorities and technical requirements. Benefits: Opportunity to work on large-scale user-behavior and machine learning datasets. High-impact role at the intersection of data science, machine learning, product, and engineering. Cross-functional collaboration with ML engineers, Product teams, and Technical Program Managers. Opportunity to influence data strategy and the development of production-level machine learning systems. Exposure to complex, multidisciplinary technology environments. Opportunity to contribute to scalable data processes and data quality standards. Potential for professional growth through collaboration across diverse technical disciplines. Inclusive environment committed to equal employment opportunities. Reasonable accommodations available throughout the application and recruitment process for qualified candidates with disabilities. External candidates may be required to attend an in-person interview at a company location as part of the selection process.

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