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RBC

Staff Data Scientist, AI Evaluations Platform

Montreal, QC, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Oct 31, 2026
Posting language: English
Posted: Oct 9, 2026

Original job description

Job Description

What is the opportunity?

RBC’s AI Group is building trusted AI capabilities for the enterprise, and evaluation is one of the core controls that makes that possible. As Staff Data Scientist, AI Evaluations, you will be a senior technical leader in the data science function responsible for how RBC measures model and agent quality, safety, risk, and performance. You will design, build, and continuously improve evaluation datasets, sourcing methods, LLM judge design, deterministic scorers, human evaluation protocols, quality benchmarks, and measurement frameworks that help AI systems move from experimentation to production with evidence and control, while providing technical guidance and mentorship to other data scientists on the team.

What will you do?

Design and drive advanced model and agent evaluation methodologies, including evaluation datasets, rubrics, LLM-as-judge methods, deterministic scorers, human evaluation, and measurement frameworks, providing technical guidance to junior team members.
Define evaluation science standards that translate model risk, responsible AI, product quality, safety, and business expectations into measurable criteria, repeatable methods, and clear evidence.
Own the end-to-end lifecycle for evaluation datasets and scorecards, including sourcing, curation, validation, quality checks, versioning, lineage, reuse, and ongoing improvement.
Design scalable evaluation approaches for generative AI and agentic systems, including task-level, workflow-level, trajectory-level, and runtime evaluation methods.
Partner with AI research, platform engineering, product, risk, governance, and business teams to embed evaluations into build, release, certification, monitoring, and recertification workflows.
Establish human evaluation and review protocols that produce reliable labels, reviewer guidance, adjudication processes, quality controls, and audit-ready evidence.
Measure and improve scorer accuracy, calibration, robustness, failure-mode coverage, and explainability across automated and human evaluation approaches.
Provide clear technical leadership, executive-ready communication, and mentorship to junior data scientists to help RBC scale trusted AI with speed, rigor, and control.
In this role, you will communicate and interact frequently with RBC partners and/or employees located across Canada and/or worldwide

What do you need to succeed?

Must Have

8+ years of experience in data science, applied machine learning, AI evaluation, ML quality, or a related technical field, including experience providing technical leadership and mentorship within a team.
Strong experience designing evaluation frameworks for ML, generative AI, or agentic AI systems, including metrics, datasets, benchmarks, rubrics, and quality measurement.
Practical experience with LLM evaluation methods such as LLM-as-judge, deterministic scoring, human evaluation, hallucination assessment, factuality assessment, safety evaluation, or model quality benchmarking.
Strong technical foundation in data science, statistics, machine learning, experimentation, data curation, Python, SQL, and modern AI/ML development practices.
Proven ability to translate governance, model risk, responsible AI, and business requirements into measurable controls, repeatable evaluation processes, and decision-ready evidence.
Strong communication and stakeholder management skills, with the ability to influence senior leaders across research, engineering, product, governance, risk, and business teams.

Nice to Have

Experience evaluating agentic AI systems, tool-calling workflows, multi-step reasoning, runtime traces, trajectory scoring, or workflow-level performance.
Experience in financial services, regulated AI, model risk management, responsible AI, enterprise governance, or audit-ready evidence processes.
Familiarity with tools and platforms such as MLflow, Langfuse, LangSmith, OpenTelemetry, Grafana, CI/CD pipelines, or comparable evaluation and observability tooling.
Publications, patents, open-source contributions, or industry work related to AI evaluation, ML quality, AI safety, applied research, or responsible AI.
Ph.D. or Master’s degree in a quantitative or technical field, such as Applied Mathematics, Engineering, Computer Science or a related computational discipline.

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
Leaders who support your development through coaching and managing opportunities
Ability to make a difference and lasting impact
Work in a dynamic, collaborative, progressive, and high-performing team
A world-class training program in financial services
Opportunities to do challenging work.

#TECHPJ

Job Skills

Big Data Analytics, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning (ML), Results-Oriented, Software Engineering, Software Product Design

Additional Job Details

Address:

6666 RUE ST URBAIN, FLOOR 3:MONTRÉAL

City:

Montréal

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-10-09

Application Deadline:

2026-10-31

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

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More about this job

Responsibilities

You will lead the design and implementation of advanced evaluation methodologies for AI models and agents to ensure quality, safety, and performance. This role involves collaborating with cross-functional teams to embed these evaluation frameworks into the end-to-end AI development lifecycle.

Requirements

Candidates must have 8+ years of experience in data science or applied machine learning with a strong foundation in AI evaluation frameworks. A postgraduate degree in a quantitative field is preferred, along with proven ability to translate governance and business requirements into measurable technical controls.

Skills

Data Science
Machine Learning
AI Evaluation
LLM Evaluation
Python
SQL
Statistics
Model Risk Management
Generative AI
Agentic AI
Data Curation
Stakeholder Management
Technical Leadership
Responsible AI
Experimentation

Benefits

Bonuses
Flexible benefits
Competitive compensation
Stock
Training program

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Machine Learning
AI Evaluation
Generative AI
Agentic AI
LLM-as-judge
Python
SQL
Model Risk Management
Responsible AI
MLflow
Langfuse
LangSmith
OpenTelemetry
Grafana
CI/CD
Data Curation
Statistics
Benchmarking
Governance
Observability
Technical Leadership
Financial Services
Model Quality
Factuality Assessment
Hallucination Assessment
Trajectory Scoring
Workflow-level Performance
Applied Mathematics
Computer Science

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