We are looking for an experienced Data Scientist GenAI Temporary assignment (Toronto) to contribute to the development of a segmentation tool based on generative artificial intelligence (GenAI). This tool leverages user engagement data to dynamically classify users and offer personalized content experiences. The role includes designing and implementing a robust framework for training GenAI models and validating the generated recommendations, enabling intelligent audience targeting.

Required Qualifications:

- Minimum of 5 years of experience in data science within an industrial environment, ideally in digital media, advertising, or marketing analytics.

- Master's degree or higher in a STEM field (statistics, mathematics, computer science, economics, or related discipline).

- Hands-on experience with generative AI models (GenAI) in development and production.

- Knowledge of Customer Data Platforms (CDP) and/or Data Management Platforms (DMP), with practical experience.

- Strong skills in SQL and Python, experience with agile practices, and collaborative coding standards.

- Proficiency in various advanced analytics techniques and machine learning algorithms.

- Keen attention to detail, methodical and rigorous approach.

- Ability to proactively identify issues and propose innovative solutions.

- Reputation for integrity, reliability, and commitment to collaborative projects.

Key Responsibilities:

- Develop a solid framework for training and validating generative AI models.

- Apply prompt engineering techniques to optimize GenAI model outcomes.

- Verify and validate data to ensure input quality and model reliability.

- Support the preparation, transformation, and enrichment of user engagement data.

- Conduct technical audits and validate models to enhance their robustness and statistical accuracy.

- Analyze and audit proof-of-concept models, proposing continuous improvements.

- Transform behavioral signals and interaction data to better reflect actual user behavior.

- Identify and apply appropriate modeling techniques for segmentation and personalization.

- Guide data engineering and variable selection, addressing data-related constraints.

- Communicate model results and their justifications to non-technical stakeholders with clear, business-contextual explanations.

We’re committed to fostering an inclusive, equitable, and accessible workplace where every team member feels valued, respected, and supported, and has the opportunity to reach their full potential. We welcome and encourage applications from people with disabilities.

Accommodations are available on request for candidates taking part in all aspects of the selection process. For a confidential inquiry, simply email your recruiter directly or [email protected] to make arrangements. If you have questions regarding accessible employment at FX Innovation please email our Human Resources Team at [email protected]