Staff Data Scientist

This is a fully remote position, open to applicants in Canada.

📋 Description

• Oversee the design, development, and assessment of sophisticated machine-learning models tailored for extensive structured and transactional data.

• Investigate and implement transformers, sequence modeling, self-supervised learning, and representation learning techniques.

• Create experiments, benchmarks, and evaluation frameworks to assess modeling methods and gauge generalization.

• Examine intricate datasets for data quality concerns, behavioral trends, modeling possibilities, and sources of bias or leakage.

• Generate reusable representations and modeling methods for subsequent use cases.

• Work in conjunction with engineering teams to reliably train, deploy, and operate models at scale.

• Collaborate with Product and domain specialists to identify practical applications and convert technical innovations into customer-facing features.

• Set standards for modeling quality, reproducibility, documentation, and experimentation practices.

• Guide and mentor data scientists and machine-learning engineers.

• Convey technical decisions, results, and trade-offs to both technical and non-technical stakeholders.

• Contribute to the machine-learning strategy and technical roadmap.

⛳️ Requirements

• Significant experience in constructing and deploying advanced machine-learning systems.

• Strong hands-on experience in various areas, including: deep learning and contemporary neural network architectures; transformer architectures, attention mechanisms, or sequence models; representation learning, embeddings, or self-supervised learning; structured, tabular, temporal, transactional, or event-based data; predictive or generative machine-learning models; controlled experiments and thorough model evaluation; large, noisy, and heterogeneous datasets; Python and modern machine-learning frameworks like PyTorch; CUDA and RAPIDS; and production machine learning.

• Experience collaborating with ML or data engineering teams.

• Background in mentoring data scientists or providing technical leadership across complex projects.

• PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, Physics, or another quantitative field, or equivalent practical experience.

• Typically 7+ years of relevant industry experience in Data Science, Machine Learning, or Applied Research, demonstrating impact at a senior or staff level.

• Solid understanding of machine-learning principles, statistics, and experimental design.

• Capability to independently lead technically complex projects from problem definition through to experimentation and delivery.

• Strong programming and data analysis capabilities.

• Ability to think critically about ambiguous issues and make practical technical choices.

• Excellent written and verbal communication skills.

• Proven track record of collaboration across Data Science, Engineering, Product, and business teams.

• Demonstrated technical leadership through mentoring, establishing standards, influencing architecture, or defining modeling strategies.

• Meet the criteria necessary to pass a full background check.

🏝️ Benefits

• Potential eligibility for bonus awards.