Data Scientist / Data Engineer

Data Scientist / Data Engineer Location:

Markham, ON

Onsite Flexibility:

Hybrid — 3 days a week in office (anchor day: Wednesday)

Contract Details

Position Type:

Contract

Contract Duration:

6 months (with potential for extension and conversion to permanent)

Pay Rate:

C$85.00–C$100.00 / Hour (CAD)

Shift / Schedule:

Monday–Friday, core business hours; overtime as needed

Travel Requirements:

Not required

Job Summary Reporting to the Senior Advanced Analytics Manager, the

Data Scientist / Data Engineer

will be conducting all analytical activities related to AML transaction monitoring systems. This role is best suited for someone with a blend of Data Engineering (60–70%) and Data Science (30–40%) skills. The focus is on Oracle migration, data quality, SQL/Python development, statistical analysis, and cross-functional collaboration, rather than machine learning. The team is supporting TD's migration from SAS-based systems to Oracle for AML/financial crime monitoring, and is looking for contractors to support this transformation project. Core Oracle migration and implementation work runs until April 2027, with interim monitoring work expected to be busiest until approximately October 2026, with ongoing support afterward. The hiring manager is looking for a full-stack data scientist who combines Data Science, Data Engineering, Data Quality, Data Exploration, and Statistical Analysis capabilities. The exact job title is not important — candidates can come from Data Scientist, Data Engineer, or Data Analyst backgrounds if they have the right experience. Fast learners with strong technical fundamentals and migration experience will be highly competitive.

Key Responsibilities

Work independently to provide analysis, design, and support of technical data management solutions on various projects ranging in complexity and size

Conduct data quality checks on raw or curated data on Oracle and Azure platforms

Conduct activities related to customer segmentation, scenario initial threshold setting, and model performance monitoring

Help maintain a structured documentation process to demonstrate an effective scenario review program to satisfy audit, compliance, and regulatory requirements

Execute quality control procedures to review end-to-end interim monitoring solutions, identify gaps, and support future-state implementation activities

Work with various business teams to help identify areas for improvement and provide insights using supporting data and models to support business strategies

Perform data quality validation, data cleansing, data stitching, and data integration

Build data engineering capabilities for combining multiple data sources

Support Oracle implementation (MVP 2) by validating data and preparing scenarios

Conduct transaction segmentation and initial threshold setting for AML monitoring scenarios

Monitor production performance, alert volumes, and suspicious transaction reports (STRs) after implementation

Analyze impacts when unusual alert patterns occur

Help develop and execute interim monitoring solutions while legacy systems are phased out

Collaborate with technology, project managers, business teams, and data teams

Required Skills

Expert-level proficiency in

Python

and

SQL

Advanced knowledge of query optimization, debugging, and automation

Strong data exploration and analysis skills, with experience working with large-scale datasets

Ability to apply statistical techniques and data mining tools to solve business problems

Strong knowledge of and experience with data-driven or data-centric projects

Data engineering experience

Data quality and data transformation

Strong statistical knowledge (for segmentation and threshold setting)

Ability to learn quickly in a changing environment

Strong collaboration and communication skills, with the ability to engage cross-functional teams, discuss complex data issues, and present findings clearly

Proven ability to work effectively within large, collaborative teams and contribute as a strong team player

Excellent multi-tasking skills: ability to adapt to and manage changing priorities

Preferred Skills

Experience with SAS, Informatica, Tableau, and other relevant data analytics tools

AML knowledge

Oracle ECM experience (not expected because it’s a niche platform)

Azure data pipeline experience

Informatica mapping knowledge

Data migration experience (strongly preferred)

Banking/financial services knowledge

Education Requirements

Master's degree in Computer Science or a related field is ideal; equivalent experience will be considered

Required Experience

5+ years of overall experience

5 years of experience with Python

5 years of experience with SQL

5 years of experience applying statistical techniques and data mining tools to solve business problems

5 years of data exploration and wrangling experience

5 years of experience in query optimization, debugging, and automation

5 years of experience working in large, data-driven batch environments

Nice-to-Have Experience

1+ year of AML experience

Experience with Tableau

Experience with SAS

1+ year of experience with Informatica

Financial institution (FI) background

Important Notes

Interview Process:

Single panel interview consisting of a Python coding test, SQL coding test, statistics questions, a case study, and a technical discussion with the hiring manager and team; conducted in person in Markham

Machine learning model development is

not

part of this role at this time; ML knowledge is helpful but will not be used until Oracle implementation is complete

The contractor will have access to customer data

About the Client This client is a

top 10 bank in Canada and North America

operating across retail, commercial, wealth management, and wholesale banking, with a presence spanning thousands of locations across North America and serving millions of clients in today's evolving financial market. Employing tens of thousands of professionals across its network, the organization offers comprehensive financial solutions at scale. Teams include data scientists, data engineers, financial crime risk specialists, technology professionals, and analytics managers who collaborate across large, cross-functional programs to support regulatory compliance, AML monitoring, and enterprise transformation initiatives.

About GTT GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.

Job Number: 26-08008

Industry:

Data & Analytics

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