Data Scientist / Data EngineerLocation: Markham, ONOnsite Flexibility: Hybrid — 3 days a week in office (anchor day: Wednesday)Contract DetailsPosition Type: ContractContract 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 neededTravel Requirements: Not requiredJob SummaryReporting 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 ResponsibilitiesWork independently to provide analysis, design, and support of technical data management solutions on various projects ranging in complexity and sizeConduct data quality checks on raw or curated data on Oracle and Azure platformsConduct activities related to customer segmentation, scenario initial threshold setting, and model performance monitoringHelp maintain a structured documentation process to demonstrate an effective scenario review program to satisfy audit, compliance, and regulatory requirementsExecute quality control procedures to review end-to-end interim monitoring solutions, identify gaps,



and support future-state implementation activitiesWork with various business teams to help identify areas for improvement and provide insights using supporting data and models to support business strategiesPerform data quality validation, data cleansing, data stitching, and data integrationBuild data engineering capabilities for combining multiple data sourcesSupport Oracle implementation (MVP 2) by validating data and preparing scenariosConduct transaction segmentation and initial threshold setting for AML monitoring scenariosMonitor production performance, alert volumes, and suspicious transaction reports (STRs) after implementationAnalyze impacts when unusual alert patterns occurHelp develop and execute interim monitoring solutions while legacy systems are phased outCollaborate with technology, project managers, business teams, and data teamsRequired SkillsExpert-level proficiency in Python and SQLAdvanced knowledge of query optimization, debugging, and automationStrong data exploration and analysis skills, with experience working with large-scale datasetsAbility to apply statistical techniques and data mining tools to solve business problemsStrong knowledge of and experience with data-driven or data-centric projectsData engineering experienceData quality and data transformationStrong statistical knowledge (for segmentation and threshold setting)Ability to learn quickly in a changing environmentStrong collaboration and communication skills, with the ability to engage cross-functional teams, discuss complex data issues, and present findings clearlyProven ability to work effectively within large, team-oriented teams and contribute as a strong team playerExcellent multi-tasking skills: ability to adapt to and manage changing prioritiesPreferred SkillsExperience with SAS, Informatica, Tableau,



and other relevant data analytics toolsAML knowledgeOracle ECM experience (not expected because it's a niche platform)Azure data pipeline experienceInformatica mapping knowledgeData migration experience (strongly preferred)Banking/financial services knowledgeEducation RequirementsMaster's degree in Computer Science or a related field is ideal; equivalent experience will be consideredRequired Experience5+ years of overall experience5 years of experience with Python5 years of experience with SQL5 years of experience applying statistical techniques and data mining tools to solve business problems5 years of data exploration and wrangling experience5 years of experience in query optimization, debugging, and automation5 years of experience working in large, data-driven batch environmentsNice-to-Have Experience1+ year of AML experienceExperience with TableauExperience with SAS1+ year of experience with InformaticaFinancial institution (FI) backgroundImportant NotesInterview 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 MarkhamMachine learning model development is not part of this role at this time; ML knowledge is helpfulbut will not be used until Oracle implementation is completeThe contractor will have access to customer dataAbout the ClientThis 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 GTTGTT 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#LI-GTT #LI-Onsite #gttca #J-18808-Ljbffr

📌 Data Scientist / Data Engineer (Markham)
🏢 Creative Solutions Services
📍 Markham