Lead Data Scientist
New
J
JobgetherConsumer technology
Based in CanadaFull-TimeLead
SalaryCompetitive annual base salary for Canada of $171,500–$202,500 CAD
Apply NowOpens the employer's application page
Job Details
- Experience
- 6+ years of professional experience scoping, building, analyzing, and deploying ML-powered systems
- Required Skills
- PythonMachine LearningSoftware Engineeringscikit-learnGenerative AIPySpark
Requirements
- Have 6+ years of professional experience scoping, building, analyzing, and deploying ML-powered systems, including models shipped to production.
- Have an advanced degree in a quantitatively rigorous discipline involving sophisticated statistical analysis, or equivalent industry experience.
- Bring strong programming experience with Python, scikit-learn, PySpark, and tools for causal inference.
- Apply software engineering practices including testing, modularization, and version control.
- Have technical training and professional experience applying modern causal inference and causal analysis techniques.
- Have experience working with existing datasets, designing instrumentation to generate new data, and building transformations for complex analyses and ML systems.
- Have hands-on experience designing, monitoring, and analyzing experiments in consumer technology environments.
- Have experience building ML systems or running experiments within B2C technology; experience with subscriptions, transactions, advertising, or other revenue-generating products is preferred.
- Have experience leveraging LLMs and generative AI for data processing, analysis, development, or other data science workflows.
- Be able to critically review AI-generated code, analyses, and models and take ownership of production outcomes.
Responsibilities
- Investigate revenue opportunities and translate findings into opportunities that can be sized, prioritized, tested, and measured.
- Design, build, deploy, and operate production ML systems, including batch inference, online services, and online learning models.
- Develop ML systems for personalization, experimentation, and automation.
- Partner with Product, Mobile Engineering, Cloud Engineering, Data Engineering, and MLOps teams to integrate ML into customer-facing experiences.
- Establish monitoring and measurement frameworks for model performance, product outcomes, and business impact.
- Implement data, code, and model lineage practices for secure, reproducible, and compliant ML lifecycles.
- Collaborate with Data Engineering to improve pipelines and the data ecosystem for experimentation and machine learning.
- Apply causal inference, experimentation, and advanced analytics to guide product and revenue decisions.
- Mentor data scientists and contribute to best practices for analytics, experimentation, and production ML development.
- Use Claude Code and other AI tools across data discovery, modeling, coding, experiment evaluation, and workflow optimization; share effective workflows with data science and engineering teams.
View Full Description & ApplyYou'll be redirected to the employer's site
