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Added 2 months ago
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Consultant / Senior Consultant, Financial Crime Analytics
Deloitte
Toronto, ON
- Full-time
Proven experience with data analytics and visualization tools such as SQL, Python, Databricks, Tableau, Power BI.
Added 2 months ago
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Senior Python Developer
Highspring
Montreal, QC
- Full-time
Highspring is seeking a Senior Python Backend Developer in permanent position to join a mobile technology team responsible for building and supporting applications that enable critical…
Added 2 months ago
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Senior Consultant - Credit Risk Modelling - Montreal
EY
Montreal, QC
- Full-time
Significant experience and proven ability to program in pertinent languages, such as Excel, SAS, SQL, R, and Python.
Added 2 months ago
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Actuarial Manager, Property & Casualty, Actuarial Insurance Solutions
Deloitte
Toronto, ON
- Full-time
Build trusted relationships with senior client stakeholders
Added 2 months ago
D
Sr Data Scientist / Power Systems Analyst
Deloitte
Toronto, ON
- Full-time
Proficiency in programming languages and tools such as Python, SQL, or similar.
Added 2 months ago
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Manager, Financial Crime Analytics
Deloitte
Toronto, ON
- Full-time
Proven experience with data analytics and visualization tools such as SQL, Python, Databricks, Tableau, Power BI.
Added 2 months ago
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Manager, AML Analytics - Financial Engineering & Modeling
Deloitte
Toronto, ON
- Full-time
Strong programming skills in Python, SQL, SAS, R, or similar technologies, with hands-on experience working with large and complex datasets. Experience with automation and advanced…
Added 2 months ago
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Consultant/Senior Consultant, Credit Risk Models - Financial Engineering & Modeling (Perm/Contract)
Deloitte
Toronto, ON
- Full-time
…model performs under stress, develop a benchmark model using Python or R by leveraging statistics, machine learning and artificial intelligence, or translate complex analyses into clear…
Added 2 months ago
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Senior Manager, Analytics Insights
Deloitte
Toronto, ON
- Full-time
Apply strong hands-on technical expertise and leadership, leveraging tools such as SQL, Python/R, and modern BI platforms, along with advanced techniques (e.g., statistical modeling,…
Added 2 months ago
Senior Manager, Resilience Engineering (Scenario Testing)
Scotiabank
Toronto, ON
Use analytical tooling (e.g., SQL, Python, data visualization platforms, monitoring and observability systems) to derive trends, correlations, and identify focus areas for testing exercises.
Added 2 months ago
OT
Sr. Software Developer
Open Text Corporation
Richmond Hill, ON
- Other
We are looking for a Senior Software Developer to design and build the integration layer between OpenText Content Management and the Microsoft ecosystem, including Microsoft Teams,…
Added 2 months ago
D
Manager, Credit Risk Models - Financial Engineering & Modeling
Deloitte
Toronto, ON
- Full-time
…model performs under stress, develop a benchmark model using Python or R by leveraging statistics, machine learning and artificial intelligence, or translate complex analyses into clear…
Added 2 months ago
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Senior Python Developer
CGI
Ottawa, ON
- Full-time
We are seeking a Senior Python Developer with expertise in cloud native development, Azure Databricks, and API engineering. This role supports the development of scalable solutions that…
Added 2 months ago
RI
Full Stack Developer (Student Co-op)
Remarcable, Inc.
Vancouver, BC
- Internship
Build and iterate on product features with guidance from senior engineers.
Added 2 months ago
Senior Analyst, Compliance Data & Automation
Questrade Financial Group
Toronto, ON
Designing, building, testing, and maintaining scripts, workflows, and automations using Python, SQL, N8N, Google Apps Script, and similar tools.
Added 2 months ago
SD
Data Scientist
Symbiotic Digital
Toronto, ON · Queen's Park Ontario Provincial Government, Ontario
- Contract
We are seeking a Senior Data Scientist to analyze complex
Added 2 months ago
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Senior Software Engineer- Big Data & Java
PointClickCare
Mississauga, ON
- $142,000 to $158,000 CAD / year
- Full-time
Experience in writing clean code that performs well at scale using languages such as Python, Java etc.
Added 2 months ago
TT
2027 BrainBox AI Intern
trane technologies
Montreal, QC
- Full-time
· Avoir de l’expérience avec des outils comme Python, SQL, Jira, Asana ou des outils semblables (un atout)
Added 2 months ago
OM
Director, Audience Strategy
Omnicom Media
Toronto, ON
- Full-time
Advise senior stakeholders using data-driven insights across audience strategy, testing, and optimization.
Added 2 months ago
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RQ11402 - Systems Testing/QA Specialist - Senior
Maarut
Toronto, ON
- Contract
of scripting languages (e.g., Python, JavaScript, Bash) for automation or
Added 2 months ago
Senior Consultant - Fraud Analytics
EY
Toronto, ON
Proficiency in SQL and experience with at least one analytical programming language or platform, such as Python, R, or SAS.
Added 2 months ago
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Manager, Risk Modelling & Analytics, Forecasting
Financeit
Remote, Canada
- Full-time
- Remote
4+ years of applied experience in building models (Python, Excel), data pipelines (dbt, SQL, Airflow), and/or automating processes would be a strong asset
Added 2 months ago
HT
Senior Data Analyst / BI Analyst
High Tech Genesis
Ottawa, ON
- Contract
We are seeking an experienced Senior Data Analyst / BI Analyst to support data transformation, reporting, and modernization initiatives. This role requires someone who can work closely with…
Added 2 months ago
Senior Data Analyst
Clutch Technologies Inc.
Toronto, ON
As a Senior Data Analyst, you'll join our data team to help build out the analytics and data infrastructure behind one of our newer business lines. You'll start by strengthening the…
Added 2 months ago
C
Senior Software Engineer, AI
Calabrio
Canada
- Full-time
Calabrio-Verint is looking for a highly skilled and experienced Senior Software Engineer, AI to perform a key role in our digital transformation program, and deliver exceptional customer…

Senior Consultant - Fraud Analytics

Toronto, ON, M5H 0B3, Canada

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Job details

Apply by: Dec 2, 2026
Posting language: English
Posted: Aug 31, 2026

Original job description

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.

Join EY and help to build a better working world.

The opportunity

We currently have career opportunities for Senior Consultants within our Canadian Fraud Risk Consulting practice with a focus on fraud analytics, detection and data science. Our team helps financial institutions transform fraud risk management through the application of data, artificial intelligence, machine learning, and advanced analytical techniques in an increasingly complex threat landscape.

Emerging technologies, evolving fraud typologies, and real-time payment ecosystems require organizations to enhance their fraud detection capabilities with sophisticated analytical solutions. We help financial institutions strengthen fraud prevention and detection using data analysis, statistical methods, machine learning, and practical improvements to fraud processes and technology.

This job posting relates to an existing vacancy within our organization.

Your key responsibilities

As a Senior Consultant, you will work directly with clients and multidisciplinary EY teams to deliver advanced analytics, machine learning, and data-driven fraud risk solutions. Responsibilities include:

Design, develop, validate, and deploy fraud detection rules and models across banking and payment products.
Analyze large and complex datasets to identify emerging fraud patterns, trends, vulnerabilities, and opportunities for enhanced fraud mitigation.
Collaborate with fraud SMEs, business stakeholders, and technology teams to translate business challenges into analytical use cases and model requirements.
Support the development of fraud risk strategies across payments, account takeover, identity fraud, synthetic identity, money movement, and emerging fraud typologies.
Develop fraud dashboards and management reporting to track fraud trends, losses, detection performance, operational outcomes, and key risk indicators.
Contribute to data preparation, feature engineering, and model monitoring activities that support sustainable fraud analytics programs.
Present analytical findings and recommendations to senior client stakeholders in a clear, business-oriented manner.
Contribute to business development activities, proposals, thought leadership, and innovation initiatives focused on fraud analytics, AI, and emerging technologies.
Evaluate fraud rules or models using measures such as fraud capture, false-positive rates, precision, recall, operational impact, and financial outcomes.

Skills and attributes for success

Advanced Analytical Mindset

Strong quantitative, statistical, and problem-solving capabilities.
Ability to transform large volumes of structured and unstructured data into actionable insights.
Passion for leveraging AI, machine learning, and advanced analytics to solve complex fraud challenges.

High-Performance Teaming

Demonstrated ability to collaborate across data science, engineering, fraud operations, and business teams.
Experience managing workstreams and contributing to project delivery within consulting or financial services environments.

Strong Communication Skills

Ability to communicate technical concepts, model outcomes, and analytical findings to both technical and non-technical audiences.
Experience creating executive-ready presentations, reports, and client deliverables.

Curiosity and Innovation

Strong interest in emerging fraud trends, AI technologies, and analytical methodologies.
Proactive approach to experimentation, innovation, and continuous learning.

Integrity and Inclusiveness

Commitment to ethical AI principles, model governance, and responsible use of data.
Ability to thrive in diverse teams and collaborative environments.

To qualify for the role you must have

At least three years of experience in fraud analytics, data science, machine learning, quantitative risk management, or advanced analytics within financial services or consulting.
Experience working with banks, credit unions, payment organizations, fintechs, or fraud risk teams.
Experience designing, testing, tuning or evaluating fraud-detection scenarios, thresholds or risk indicators.
Strong understanding of fraud detection methodologies, fraud operations, transaction monitoring, or financial crime analytics.
Experience manipulating and analyzing large-scale datasets and developing practical analytical solutions.
Proficiency in SQL and experience with at least one analytical programming language or platform, such as Python, R, or SAS.
Experience with PowerBI.

Ideally, you'll also have

Bilingual (English/French) considered an asset.
Hands-on experience developing and validating predictive models using Python, R, SQL, SAS, or similar analytical tools.
Experience with payment fraud, card fraud, account takeover, digital banking fraud, or first-party fraud.
Knowledge of MLOps, model governance, explainable AI, and model monitoring practices.
Exposure to graph analytics, network analytics, entity resolution, or behavioural analytics.
Exposure to practical uses of generative AI or AI-assisted analytics in fraud risk management is an asset.
Experience applying supervised and unsupervised machine learning techniques - including gradient boosting, random forests, anomaly detection, clustering, and neural networks - to fraud detection problems is considered an asset.

What we offer

At EY, our Total Rewards package supports our commitment to creating a leading people culture built on high-performance teaming, where everyone can achieve their potential and contribute to building a better working world for our people, our clients and our communities. We offer a competitive compensation package where you'll be rewarded based on your performance and recognized for the value you bring to our business. Our Total Rewards package includes comprehensive medical, prescription drug and dental coverage, a defined contribution pension plan, a vacation policy, firm-paid days, statutory holidays and paid personal days based on province of residence, and a range of programs and benefits designed to support your physical, financial and social well-being. Plus, we offer:

Support, coaching and feedback from engaging colleagues
Opportunities to develop new skills and progress your career
The freedom and flexibility to handle your role in a way that's right for you

EY reports salary ranges in accordance with applicable provincial pay transparency legislation. Individual salaries within the anticipated salary ranges noted below are determined through a wide variety of factors including but not limited to internal equity, education, relevant experience, knowledge, and applicable skill sets.

Toronto: $90,500 to $136,000

Inclusiveness at EY

Inclusiveness is at the heart of who we are and how we work. We’re committed to fostering an environment where differences are valued, policies and practices are equitable, and our people feel a sense of belonging. We embrace diversity and are committed to combating systemic racism, advancing gender equity and women in leadership, advocating for the 2SLGBTQIA+ community, promoting our neuroinclusion and accessibility initiatives, and are dedicated to amplifying the voices of Indigenous peoples (First Nations, Inuit, and Métis) nationally as we strive towards reconciliation. Our diverse experiences, abilities, backgrounds, and perspectives make our people unique and help guide us. Because when people feel free to be their authentic selves at work, they bring their best and are empowered to build a better working world.

Learn about our commitment to Inclusiveness at https://www.ey.com/en_ca/about-us/corporate-responsibility/equity

EY | Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

At EY, we use artificial intelligence (AI) tools as one element of our recruitment process to enhance efficiency and improve the candidate experience. While AI supports us in our process, human judgment and decision-making remain integral in our candidate experience. We are committed to the responsible use of AI, and our practices are continuously reviewed and refined to ensure they align with ethical principles and regulatory requirements.

To all recruitment agencies: EY does not accept unsolicited resumes from recruitment agencies. Any resumes submitted without a prior agreement or request from our hiring team will not be considered. EY is not responsible for any fees related to unsolicited resumes.

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More about this job

Responsibilities

You will design, develop, and deploy advanced fraud detection models while collaborating with multidisciplinary teams to translate business challenges into analytical solutions. Additionally, you will analyze complex datasets to identify emerging fraud patterns and present actionable findings to senior client stakeholders.

Requirements

Candidates must have at least three years of experience in fraud analytics, data science, or quantitative risk management within financial services or consulting. Proficiency in SQL and at least one analytical programming language such as Python, R, or SAS is required.

Skills

Fraud analytics
Data science
Machine learning
SQL
Python
R
SAS
PowerBI
Statistical methods
Risk management
Data visualization
Financial crime analytics
Predictive modeling
Fraud detection
Quantitative analysis
Communication

Benefits

Medical coverage
Prescription drug coverage
Dental coverage
Vacation policy
Firm-paid days
Statutory holidays
Paid personal days

Visa sponsorship

Not detected in the job text

Keywords

Fraud Analytics
Data Science
Machine Learning
SQL
Python
R
SAS
PowerBI
Financial Institutions
Risk Management
Predictive Models
Fraud Detection
Data Analysis
Statistical Methods
Artificial Intelligence
Fraud Prevention
Transaction Monitoring
Financial Crime
MLOps
Model Governance
Explainable AI
Graph Analytics
Anomaly Detection
Neural Networks
Consulting
Banking
Payment Ecosystems
Feature Engineering
Quantitative Risk Management
Data-driven

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