Senior Staff Data Scientist - Consumer Relevance in Canada Creek, Nova Scotia at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Staff Data Scientist - Consumer Relevance in Canada.

This role sits at the heart of a large-scale consumer platform where understanding and improving content relevance directly shapes how millions of users discover information and communities. You will act as a technical authority on ranking, recommendation, and search evaluation, defining how relevance is measured across highly interconnected systems. The position focuses on building rigorous metrics frameworks, experimentation methodologies, and causal analysis approaches to evaluate content quality and user satisfaction. You will partner closely with ML engineers, product teams, and leadership to translate data-driven insights into product strategy. This is a highly influential role where your work will guide how feeds, search, and recommendations evolve at scale. The environment is research-driven, fast-paced, and deeply rooted in experimentation and statistical rigor.

• Serve as the technical authority on relevance metrics and evaluation methodologies across feeds, search, and recommendation systems
• Design and develop offline and online evaluation frameworks to measure ranking quality and long-term user outcomes
• Build robust metrics systems to capture content quality, user satisfaction, retention, and community health signals
• Design and analyze large-scale experiments, accounting for network effects, spillovers, and ranking system biases
• Identify opportunities to improve measurement frameworks and unlock previously unmeasurable product insights
• Partner with ML engineers and product teams to translate model performance into user-facing impact and product decisions
• Influence product strategy for consumer relevance through deep analytical insights and experimentation results
• Mentor and guide data scientists on causal inference, experimentation design, and relevance evaluation best practices

• Ph.D. or M.S. in Statistics, Computer Science, Economics, Information Retrieval, or a related quantitative field
• For M.S.: 12+ years of relevant industry experience in data science or relevance/ranking-focused roles
• For Ph.D.: 8+ years of relevant industry experience in applied science or ranking/recommendation systems
• Deep expertise in metrics design and evaluation for ranking, recommendation, or search systems
• Strong background in causal inference, experimental design, and counterfactual evaluation techniques
• Experience working with large-scale user-generated content or social platforms is highly desirable
• Strong proficiency in SQL and programming languages such as Python and/or R
• Ability to influence product and technical strategy through data-driven insights
• Excellent communication skills for explaining complex statistical and ML concepts to diverse stakeholders
• Experience mentoring data scientists and building organizational expertise in experimentation and relevance systems

• Global benefits package supporting work, wellness, and professional development
• Comprehensive medical, dental, and vision coverage with additional health spending accounts
• Mental health, coaching, and wellbeing support programs
• Family planning and gender-affirming care benefits
• Retirement savings plan with employer matching contributions
• Income protection and support programs
• Flexible vacation policy and paid volunteer time off
• Generous paid parental leave