Senior Analyst, Payments Data Intelligence

Role overview

Data ingestion and quality

• Design and execute SQL and Python scripts to ingest, transform, and normalize multi-rail transaction data and external feeds.
• Maintain automated validation pipelines, schema enforcement, anomaly flags, and reliability scoring before modeling.
• Build scalable, documented multi-rail data structures in Google Cloud Platform, including BigQuery.
• Prepare, cleanse, normalize, and reconcile payment and external datasets for modeling.
• Create repeatable input-quality checks and documented workflows for new data sources.

Analytics and modeling

• Analyze payments data to produce business insights and interpret trends.
• Conduct time-series decomposition, cross-rail migration analytics, correlation mapping, and feature engineering.
• Build reproducible pipelines modeling payment volume, value, structural shifts, and velocity across rails.
• Prepare outputs for back-testing, performance evaluation, and stress or scenario analysis.
• Integrate model explainability, attribution, and pricing-related outputs into downstream tools and executive reporting.

Technical workflow and collaboration

• Manage analytics environment configuration, query performance, and computational efficiency across BigQuery, Cloud Storage, Vertex AI tooling, and related tools.
• Maintain repeatable deployment steps and input-quality checks and basic performance monitoring for production models.
• Establish SQL and Python coding standards, documentation, and reproducible workflows; prepare model-validation summaries and methodology briefs.
• Work with the Lead Data Scientist, Data Engineering, Product teams, and stakeholders; explain technical and statistical findings in plain language.

Qualifications

• Undergraduate or graduate degree in Data Science, Computer Science, Mathematics, Statistics, Economics, Finance, or a related quantitative discipline.
• At least five years of experience in data analytics, data science support, or quantitative analysis.
• Strong statistical grounding in time-series concepts, correlation analysis, and feature engineering.
• Proficiency in Python and SQL; familiarity with BigQuery or equivalent cloud analytics environments.
• Hands-on data validation, cleansing, normalization, and quality-control experience; ability to brief non-technical stakeholders.
• Eligibility to obtain and maintain Government of Canada Reliability Status Clearance and complete enhanced background checks.
• Vertex AI, model deployment, workflow automation, explainability, or payment infrastructure experience is an asset.

Work arrangement

• The role offers a flexible hybrid remote and office environment.

Compensation and benefits

• Target starting rate is $100,300, with flexibility based on experience and qualifications.
• Benefits include an annual variable bonus, defined-contribution pension, health and dental coverage, paid time off, and professional development opportunities; eligibility conditions apply.