Jobber is hiring a Staff Data Scientist Applied ML in Kitchener!
Jobber is hiring a Staff Data Scientist, Applied Machine Learning in Kitchener for a senior individual-contributor role with substantial architectural ownership. The position sits within Strategy and Analytics and focuses on automated decisioning systems, including SignalGraph, Jobber's company-wide metric graph, and retrieval-augmented generation built on top of it. The successful candidate will train and evaluate models using graph representation learning, transformer architectures, and ranking, then engineer them for reliable real-time use inside Jobber's product. This is a hands-on technical leadership role: the person will set standards for how ML systems are built, evaluated, monitored, and trusted, while mentoring other scientists and influencing senior partners. Jobber emphasizes transparent compensation, professional growth, and an inclusive culture. The salary range is stated as $145,900 to $197,400 CAD, with a midpoint of $171,600 CAD; the posting notes that offers typically start around the midpoint for established hires, with the upper end reserved for demonstrated deep expertise and lasting impact.
Key responsibilities
- Build, improve, and maintain SignalGraph, including metric contracts, segment and causal-edge catalogs, Neo4j operation, series refresh pipelines, and investigation diagnostics.
- Design, build, and evaluate RAG systems over the metric graph, owning retrieval quality, context management, and evaluation harnesses.
- Own production ML end-to-end: training pipelines, real-time serving, monitoring, drift detection, and retraining.
- Establish systematic evaluation and regression testing so model and LLM quality is measured and defended over time.
- Set MLOps and ML engineering standards, shape feature-store and platform direction, review peers' work, and mentor scientists on graph and deep learning methods.
- Partner with senior leadership and cross-functional teams, present work, defend assumptions, and align stakeholders on data meaning and decisions.
- Track AI/ML developments and translate them into shipped capabilities.
Key requirements
- End-to-end production ML experience with models deployed to real users, including retraining, drift, and technical debt.
- Strong statistics foundation: bias/variance, loss-function justification, and signal-versus-noise reasoning.
- Expert SQL and production-grade Python.
- Depth in deep learning, transformers/BERT-family models, RNNs/CNNs, ranking, and representation learning, plus hands-on LLM production work including RAG and context management.
- Experience with custom or asymmetric loss functions tied to the business cost of errors.
- Experience with large production data and platforms such as Snowflake, Apache Airflow, and AWS; GCP or Azure equivalents considered.
- Strong communication, stakeholder alignment, and influence without authority.
- Commitment to quality over shipping speed and deep understanding of one's own code.
- Seniority: Staff
- Work mode: Not specified; Kitchener location
- Salary: $145,900–$197,400 CAD
- Key skills: Python, SQL, deep learning, transformers, LLMs, RAG, ranking, representation learning, graph representation learning, MLOps, model serving, monitoring, drift detection, evaluation, Snowflake
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