Data Scientist

Role overview

This is a remote-first Data Scientist opportunity for candidates based in Canada. The role is being managed on behalf of a partner employer, and all application review and next steps are handled by that company.

You will join a fast-moving, product-focused setting where data science has a direct effect on customer experience and overall business performance at scale. The position involves building and deploying machine learning solutions for personalization, search, and recommendation capabilities used by a worldwide audience. It blends advanced statistical analysis, Python development, and cloud-based tooling to solve meaningful real-world problems. You will partner with product and engineering teams to turn complex datasets into practical insights and production-ready systems.

The environment is collaborative, distributed, and centered on measurable results. This opportunity suits someone who wants to own machine learning systems from end to end and see tangible business outcomes from their work.

Key responsibilities

• Create, deploy, and operationalize machine learning models that strengthen personalization, ranking, and recommendation experiences.
• Develop data-driven algorithms that improve user engagement and support stronger conversion performance.
• Use statistical techniques and data mining approaches to uncover insights from large datasets.
• Work with engineering and product stakeholders to embed ML models into production environments while maintaining scale and stability.
• Track model performance over time and refine solutions using live data and commercial feedback.
• Convert business challenges into analytical and machine learning approaches tied to measurable KPI impact.
• Support scalable ML workflows through cloud infrastructure and data pipeline work.
• Help build experimentation and A/B testing setups to measure model impact.

Requirements

• At least 2 years of experience in a Data Scientist, Quantitative Analyst, Quantitative Researcher, or comparable analytical position.
• Strong command of Python and common data science libraries such as pandas, NumPy, and scikit-learn or equivalent tools.
• Solid understanding of probability, statistics, machine learning, and linear algebra.
• Demonstrated success applying ML models to business problems with measurable impact on revenue or key metrics.
• Working knowledge of SQL and relational databases.
• Experience with cloud environments such as AWS, GCP, or Microsoft Azure is highly preferred.
• Exposure to productionizing ML models and working across full data science pipelines.
• Comfort operating in a fast-paced, product-led environment with cross-functional collaboration.
• Strong communication ability and skill in explaining technical topics to non-technical audiences.
• Bachelor’s or Master’s degree in Applied Mathematics, Computer Science, Engineering, Financial Engineering, or another quantitative discipline.
• Using AI tools or agents within the development workflow is an added advantage.
• Knowledge of Apache Spark and/or experience in the gaming sector is a plus.

Benefits

• Fully remote setup with flexible working arrangements.
• Competitive compensation with quarterly performance-linked bonuses.
• 28 days of paid annual leave.
• Flexible schedule with core availability expected between 10am and 3pm local time.
• High-end equipment provided for work use.
• Annual company retreats for collaboration and networking.
• Referral and performance-based bonus schemes.
• Opportunity to work on large-scale machine learning systems that influence business outcomes directly.
• Strong focus on professional development and exposure to modern ML and cloud technologies.

Application and hiring process

This role is promoted through a partner company that manages applications and subsequent hiring steps. Applications are reviewed using an AI-assisted matching process designed to assess fit against the core role criteria in a fair and objective way. The strongest matches are forwarded to the hiring company, which handles interviews, assessments, and final hiring decisions.

Privacy and AI notice

By applying, candidates acknowledge that personal data will be processed to evaluate suitability for the role and to share relevant information with the employer. This is based on legitimate interest and pre-contractual steps under applicable data protection laws, including GDPR. Applicants may request access, correction, deletion, or objection rights at any time.

AI tools may be used to support parts of the hiring workflow, including application review, resume analysis, response assessment, and identifying possible inconsistencies in submitted materials. These tools assist the recruitment process but do not replace human judgment, and final hiring decisions are made by people.