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Ux Researcher jobs in United States

Lead Data Scientist, Fraud Applied AI & Innovation

RBC

Toronto
On-site
CAD 90,000 - 140,000
Yesterday
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Remote Data Scientist — Azure, Python & SQL

Source Code

Toronto
Remote
CAD 80,000 - 120,000
Yesterday
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Data Scientist (Azure, Python, and SQL) - Toronto, ON

Source Code

Toronto
Remote
CAD 80,000 - 120,000
Yesterday
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Data Scientist, Customer Journey — Build Dashboards

Noibu

Ottawa
On-site
CAD 100,000 - 125,000
Yesterday
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Data Scientist - Customer Journey (Ottawa)

Noibu

Ottawa
On-site
CAD 100,000 - 125,000
Yesterday
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Associate Scientist, Cell & Gene Therapy Analytics

OmniaBio

Hamilton
On-site
CAD 60,000 - 75,000
Yesterday
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Associate Scientist, Analytical Science & Technology (ASAT)

OmniaBio

Hamilton
On-site
CAD 60,000 - 75,000
Yesterday
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Remote Oncology Clinical Researcher for AI Trials

Alignerr

Edmonton
Remote
CAD 60,000 - 80,000
Yesterday
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Oncology Clinical Researcher

Alignerr

Edmonton
Remote
CAD 60,000 - 80,000
Yesterday
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PhD Student Researcher - Real-World AI/ML (Canada)

Google

Montreal (administrative region)
On-site
CAD 115,000
Yesterday
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Student Researcher, PhD, Winter/Summer 2026

Google

Montreal (administrative region)
On-site
CAD 115,000
Yesterday
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Senior Data Scientist: Real-World ML for Production Systems

Palitronica Inc.

Southwestern Ontario
On-site
CAD 100,000 - 125,000
Yesterday
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Senior Data Scientist

Palitronica Inc.

Southwestern Ontario
On-site
CAD 100,000 - 125,000
Yesterday
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Hybrid Data Scientist — Predictive Analytics for Impact

Allstate Insurance Company

Markham
Hybrid
CAD 80,000 - 130,000
Yesterday
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Data Scientist

Allstate Insurance Company

Markham
Hybrid
CAD 80,000 - 130,000
Yesterday
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Generative AI Scientist: Fulfillment Optimization

Amazon

Vancouver
On-site
CAD 100,000 - 140,000
Yesterday
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Applied Scientist II ML/AI, Fulfillment Planning and Execution Science - Fulfillment Optimizati[...]

Amazon

Vancouver
On-site
CAD 100,000 - 140,000
Yesterday
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Cloud Data Scientist & Analytics Engineer

Source Code

Toronto
Hybrid
CAD 70,000 - 90,000
Yesterday
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Research Associate - BRaIN (Research Institute)

RI-MUHC | Research Institute of the MUHC | #rimuhc

Montreal (administrative region)
On-site
CAD 54,000 - 101,000
Yesterday
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Neuroscience Research Associate: Brain, Language & Music

RI-MUHC | Research Institute of the MUHC | #rimuhc

Montreal (administrative region)
On-site
CAD 54,000 - 101,000
Yesterday
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Senior AI Scientist – GenAI & Digital Pharma Transformation

BioTalent Canada

Toronto
On-site
CAD 80,000 - 110,000
Yesterday
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Data Scientist

BioTalent Canada

Toronto
On-site
CAD 80,000 - 110,000
Yesterday
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Research Scientist

Sixone Labs

British Columbia
On-site
CAD 70,000 - 90,000
2 days ago
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Data Scientist

Medavie

New Brunswick
On-site
CAD 88,000 - 100,000
2 days ago
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Senior Applied Machine Learning Scientist, Generative AI (4047)

TD Bank

Canada
On-site
CAD 156,000 - 190,000
2 days ago
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Lead Data Scientist, Fraud Applied AI & Innovation
RBC
Toronto
On-site
CAD 90,000 - 140,000
Full time
Yesterday
Be an early applicant

Job summary

A leading financial institution in Toronto seeks a skilled Machine Learning Lead to drive advancements in fraud management through predictive modeling. You'll lead the development of fraud detection strategies and collaborate with diverse teams to ensure effective model validation. With 5+ years in Machine Learning and programming expertise, including Python and R, you will significantly enhance fraud detection processes. This position offers a full-time role in a dynamic environment focused on innovative solutions.

Benefits

Comprehensive Total Rewards Program
Supportive leaders
Opportunity for impactful work

Qualifications

  • 5+ years of experience in Machine Learning, data mining, and statistics.
  • Strong practical knowledge of programming languages: Python, R, SQL, etc.
  • Working knowledge of Big Data Framework (Hadoop, etc.).
  • Strong understanding of version control (Git/GitHub).
  • Proven ability to perform complex data analysis on large volumes of data.

Responsibilities

  • Lead the development and implementation of the Data Science Machine Learning strategy.
  • Develop supervised fraud detection models and explore unsupervised detection applications.
  • Collaborate with partners in Fraud IT on the fraud detection ecosystem.
  • Work with EMRM for efficient model validation.

Skills

Machine Learning
Data Mining
Statistics
Python
R
SQL
Big Data Framework
Problem Solving
Quantitative Skills
Communication

Education

Bachelor’s degree in a quantitative discipline

Tools

Docker
Kubernetes
Azure
AWS
OpenShift
Job description
Job Description
What's the opportunity?

You will lead Fraud Management (FM) Machine Learning (ML) and Artificial Intelligence (AI) advancements, develop strategy for predictive fraud detection ML models and explore ML/AI technique application. You will set standards for ML model development, ensuring consistency, accuracy and repeatability, collaborate with partners and work with Fraud Strategy, Fraud IT and Enterprise Model Risk Management (EMRM) on emerging fraud risks, solution design and model validation frameworks. You will fully comprehend the technical architecture supporting the Fraud decisioning ecosystem and how it supports DSA detection requirements. As a Subject Matter Expert (SME) on FM initiatives, you will collaborate with stakeholders at varying levels of seniority.

What will you do?
  • Lead the development and implementation of the Data Science Machine Learning (ML) strategy and act as key point of contact for all ML models
  • Develop supervised fraud detection models and explore opportunities for unsupervised/anomaly detection applications
  • Plan timelines, resource allocation, standards and best practices for ML model development with DS&I and be responsible for technical validation exercises for new model deployments
  • Collaborate effectively with partners in Fraud IT on continuous improvement of the fraud detection ecosystem, understanding the technical requirements and their impact on the business users in DSA
  • Work with EMRM to enable efficient model validation and develop a strong relationship with Fraud Strategy partners focused on identifying emerging fraud risks and how the application of ML can minimize these risks
  • Identify opportunities and develop solutions to automate/enhance processes through analytical tools and workflows; and utilize technology tools to build the most effective solution; Python, R, Spark, PySpark, etc.
  • Provide thought leadership to support Fraud Management’s key priorities where there is a dependence on data analytics, machine learning or data engineering
  • Leverage expertise with ML and programming to provide support to the rest of the DSA team as required
What you need to succeed
Must have
  • 5+ years of experience in Machine Learning, data mining and statistics
  • Strong practical knowledge of, and proven experience with, analytical software packages and programming languages: Python, R, SQL, etc.
  • Working knowledge of Big Data Framework (Hadoop, etc.)
  • Strong understanding of version control (Git/GitHub)
  • Strong problem solving, research and quantitative skills
  • Exceptional time management and organizational skills, ability to manage multiple projects simultaneously and prioritize workload effectively
  • Proven ability to perform complex data analysis on large volumes of data
  • Professional oral and written communication and presentation skills, including the ability to effectively communicate analytical recommendations to both technical and non-technical audiences.
  • Knowledge of Canadian banking and payment industry, payments transaction data and financial fraud
  • Bachelor’s degree in a quantitative discipline
Nice to have
  • Graduate degree in a quantitative discipline
  • Experience with Docker and Kubernetes
  • Experience with Cloud technologies (Azure, AWS, OpenShift)
  • Prior experience in fraud detection and data analytics
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
  • Leaders who support your development
  • Ability to make a difference and lasting impact
  • Opportunity to take on progressively greater accountabilities
Job Skills

AI Agents, Big Data Management, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Python (Programming Language)

Additional Job Details

Address: YORK MILLS CENTRE, 36 YORK MILLS RD:TORONTO

City: Toronto

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: PERSONAL & COMMERCIAL BANKING

Job Type: Regular

Pay Type: Salaried

Posted Date: 2026-01-29

Application Deadline: 2026-02-13

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

Inclusion and Equal Opportunity Employment

At 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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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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