LONG TERM CONTRACT – W2/C2C

Interview process: 15 Min phone call with recruiter, 90 Min technical interview/ Project Interview, 60 Min client interview – hired.
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Main skills: Data Engineering, Google Cloud, BigQuery, NumPy, Pandas, Python

• Domain/Industry: Retail/digital media, marketing or advertising is strongly preferred

Job Description: We’re looking for a Senior Data Scientist to join our team and lead the development of machine learning models for campaign measurement and audience prediction. This role combines analytical expertise with hands-on development to drive our advertising effective solutions. You will have an opportunity to work at the forefront of retail media advertising technology, to collaborate with an innovative team dedicated to excellence. Our environment fosters growth through challenging projects, provides access to cutting-edge tools and methodologies, and enables you to create solutions that drive measurable business impact in the digital advertising space.

REQUIREMENTS

• Degree in computer science, statistics or machine learning (Master’s degree is preferred).
• Overall IT Experience: 7+ Years
• 5+ years of experience in data science within retail/digital media, marketing or advertising.
• Strong proficiency with Python ecosystem (NumPy, Pandas) and SQL.
• Practical expertise with CI/CD tools (Git, GitHub, GitHub Actions).
• Hands-on background with Google Cloud technologies (BigQuery, Vertex AI, GCS).
• TensorFlow/PyTorch knowledge highly desirable.
• Google Cloud or AWS certifications a plus.

REQUIRED SKILLS

Senior Develope Senior Network Enginee

ROLE: SENIOR DATA SCIENTIST

Location: Toronto Downtown, ON – Hybrid (4 days/week - Onsite)

RESPONSIBILITIES

• Develop and maintain ML models for measuring incremental impact of digital advertising campaigns.
• Build classification and regression models using Google Cloud tools (BigQuery, Vertex AI) and Python libraries (Pandas, NumPy, SciKitLearn).
• Implement advanced media mix and multi-touch attribution models to optimize spending.
• Design frameworks for campaign measurement using synthetic controls and lift measurement techniques.
• Collaborate on MLOps integration, including CICD pipelines and monitoring systems.
• Perform complex data analysis and communicate findings to diverse stakeholders.