About the role

You will own the end-to-end data science lifecycle, from problem framing and model development to production deployment and monitoring. You will collaborate with business partners to translate ambiguous requirements into actionable machine learning solutions while mentoring junior team members.

What they look for

Machine Learning Python R Data Science Statistical Modeling LLM Generative AI RAG pipelines Data visualization Predictive modeling MLOps Feature engineering Model evaluation Big data Financial services Mentorship

Requirements

Candidates must hold a Master's or PhD in Computer Science, Mathematics, or Statistics with over 10 years of IT experience. You need at least 3 years of experience building and deploying machine learning models in production environments, including proficiency with LLMs and statistical rigor.

Benefits

401(k) program with company-matching contributions Health insurance Dental insurance Vision insurance Life insurance Disability insurance Paid time off Professional development coaching

Full description

Job Description

What is the opportunity?

In this role as a Lead Data Scientist you will analyze, design and implement data science / machine learning solutions using RBC’s enterprise suite of analytics tools. USWM Applied AI group specializes in taking full advantage of large data sets to explore and discover new insights that would have not been possible with traditional analytics. Leveraging leading edge technologies and capabilities, the group applies machine learning and statistical modelling techniques to help RBC understand the changing business environment, discover new growth opportunities and determine where business improvements can be made.

This is a senior individual contributor role on a greenfield Applied AI squad. You will own the full data science lifecycle — from problem framing and exploratory analysis through model development, evaluation, and production performance. You'll work alongside AI engineers and MLOps to bring models and data-driven features into real financial services workflows. This isn't a notebook-and-dashboard role: you write production Python, collaborate closely with engineering, and take clear ownership of model quality and business outcomes. Financial domain knowledge, statistical rigor, and the ability to translate ambiguous business questions into solvable ML problems are equally important as technical depth.

What will you do?

Collaborate with key business partners and stakeholders to understand business objectives/opportunities and problem statements in order to provide solutions that align to business needs that are actionable with a tangible outcome

Frame ambiguous business problems into well-defined ML and AI problem statements with measurable success criteria.

Own end-to-end model development — feature engineering, training, evaluation, and production handoff.

Build and evaluate LLM-augmented workflows — combining classical ML signals with generative AI where appropriate

Prepare and transform data (structured/non-structured)

Design and maintain offline and online evaluation frameworks — ensuring model quality before and after deployment

Prepare, integrate large and varied datasets and implement statistical and ML models using Python and R.

Leverage visualization tools/packages to story-tell and to convey data-driven insights with actionable recommendations to key stakeholders

Quickly learn new methods, tools and technologies presented in research communities to implement, adapt and innovate

Effectively communicate findings to business partners and executives.

Developing predictive data models, quantitative analyses and visualization of targeted, big data sources.

Lead and mentor junior Data Scientists throughout the ML lifecycle.

Monitor production models for drift and performance. Build dashboards and communicate insights.

Document experiments and support AI governance. Present findings to technical and business stakeholders.

What do you need to succeed?

Must-have

Master’s in computer science or PHD in Computer Science with Specialization in Data Science, Mathematics & Statistics.

10+ years total IT experience with 3+ years building and deploying ML models in production environments — not just notebooks

Experience with model evaluation rigor — holdout sets, cross-validation, leakage prevention, business metric alignment

Practical understanding of LLM capabilities and limitations — knows when to use generative AI vs. classical ML vs. deterministic rules

Experience building or evaluating RAG pipelines or LLM-augmented analytics workflows — even if not the primary architect

Comfortable working within an enterprise LLM gateway environment — model routing, cost awareness, token management

Worked in a regulated or compliance-sensitive environment — model documentation, auditability, and explainability requirements

Excellent analytical, problem solving, time management and organizational skills.

Can distinguish when a problem needs ML vs. a simpler rule-based approach — avoids over-engineering

Familiarity with LLM evaluation frameworks — RAGAS, DeepEval, LLM-as-judge, or equivalent golden dataset approaches.

Understands hallucination risks and validation strategies for LLM outputs used in business-critical decisions.

Comfortable working within an enterprise LLM gateway environment — model routing, cost awareness, token management.

Experience in programming, scripting languages and data visualization.

Nice to have:

Financial services domain — wealth management, portfolio analytics, risk scoring, client segmentation, or fraud detection experience.

Experience with NLP pipelines for financial document understanding, summarization, or entity extraction.

Familiarity with A/B testing and causal inference for evaluating model interventions in production.

Databricks or Snowflake ML for large-scale feature computation and model training

Exposure to graph-based analytics or network analysis for relationship modeling

MLflow, Weights & Biases, or equivalent for experiment tracking and model registry

Familiar with a Linux environment and shell scripting.

Familiar with data extract, transform, and load processes with a variety of data types.

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 include competitive compensation and flexible benefits, such as 401(k) program with company-matching contributions, health, dental, vision, life, disability insurance, and paid-time off.

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.

Opportunities to do challenging work.

Opportunities to build close relationships with clients.

The expected salary range for this particular position is $100,000 - $170,000, depending on your experience, skills, and registration status, market conditions and business needs.

You have the potential to earn more through RBC’s discretionary variable compensation program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.

RBC’s compensation philosophy and principles recognize the importance of a highly qualified global workforce and plays a critical role in attracting, engaging and retaining talent that:

Drives RBC’s high-performance culture

Enables collective achievement of our strategic goals

Generates sustainable shareholder returns and above market shareholder value

LI-POST

TECHPJ

Job Skills

Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)

Additional Job Details

Address:

250 NICOLLET MALL:MINNEAPOLISCity:

MinneapolisCountry:

United States of AmericaWork hours/week:

40Employment Type:

Full timePlatform:

WEALTH MANAGEMENTJob Type:

RegularPay Type:

SalariedPosted Date:

2026-08-07Application Deadline:

2026-08-28Note: 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.

Join our Talent Community

Stay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you.

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.