1 месяц назад
Lead Data Scientist (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead Data Scientist (AI): Guiding client decisions across AI, analytics, data engineering, and data strategy while building end-to-end data pipelines and scalable data products with an accent on experimental design, recommender systems, machine learning, and production-quality dashboards. Focus on solving complex cross-domain business problems, delivering measurable impact through analysis and data products, and leading high-performance data science teams.
Location: Toronto, Canada
Company
is a Toronto-based consulting firm serving startups and Fortune 500 companies with engineering, data, and analytics capabilities.
What you will do
- Partner with client executive and technical teams to guide decisions across AI, analytics, data engineering, and data strategy.
- Identify and champion projects that solve complex problems across multiple business domains.
- Apply experimental design, recommender systems, machine learning, and fundamental data science methods to improve client businesses.
- Design and implement end-to-end data pipelines, including models, tables, schemas, and ETL solutions.
- Build actionable KPIs, production-quality dashboards, analytical deep dives, and scalable data products.
- Provide technical leadership and mentor internal and client-facing teams.
Requirements
- Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Statistics, or a related field.
- 3–7 years of commercial data science experience solving high-impact business problems.
- At least 1 year leading and maintaining high-performance data science teams.
- Extensive Python experience with strong object-oriented programming fundamentals.
- Experience with data pipelines, ETL design, data products, and business-impact analysis.
- Working knowledge of Snowflake and the ability to communicate with technical and non-technical audiences.
Nice to have
- DevOps experience.
- Experience creating data product strategies, launching products, and iterating after release.
Culture & Benefits
- Competitive compensation.
- Opportunities to work on projects aligned with individual interests and skills.
- Accountability-focused environment without micromanagement.
- Collaboration with engineers and data scientists from major technology companies.
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