Flinks

Flinks

Flinks is a top financial data company empowering businesses with bank account connectivity, data insights, and open banking success.

Capital Markets
51-250
Founded 2016
$14M raised

Description

  • Own machine-learning models from problem framing and design through training, deployment, and production-quality monitoring.
  • Write design documents and RFCs to define model approaches and technical specifications.
  • Build training pipelines and package models for deployment on the shared platform operated by Data Engineering.
  • Monitor model drift, performance, and quality, and determine when retraining is needed.
  • Run rigorous evaluation using experimental design, statistical validation, drift detection, and champion-challenger promotion.
  • Collaborate with Data Engineering, backend, product, and QA teams on contracts, deployment, rollout, and integrations.
  • Develop and maintain model-performance, PSI/drift, and category-distribution monitoring tooling.
  • Contribute to live ML systems such as transaction categorization, reversal detection, NER parsing, payments risk forecasting, and enrichment models.
  • Use AI-assisted development to accelerate implementation and experimentation.
  • Connect model improvements to business outcomes such as risk reduction, enrichment accuracy, customer adoption, operational efficiency, and revenue.

Requirements

  • 6-8 years of experience building and shipping machine-learning models.
  • Experience taking models to production yourself, including training pipeline, served endpoint, and monitoring.
  • Bachelor's degree in a quantitative field such as Computer Science, Statistics, Applied Mathematics, or related.
  • Master's degree or PhD is an asset, but not required.
  • Production-grade Python experience is non-negotiable.
  • Strong foundation in data science and machine learning.
  • Ability to deploy a model as a live, monitored service.
  • Must be legally authorized to work in Canada.
  • Experience with the listed stack is helpful, including SQL, Google Cloud Platform, BigQuery, PyTorch, HuggingFace, MLflow, Kubeflow, FastAPI, containerized deployment, and Azure DevOps.
  • Notebook-only or research-only experience is not a fit for this role.

Benefits

  • Compensation of $120,000 to $160,000 CAD annually for experienced, qualified senior hires in Canada.
  • Health and dental coverage starting on day 1.
  • Flexible paid time off (FTO).
  • Remote work environment with frequent in-person gatherings and activities.
  • Career development, learning opportunities, and growth.
  • Accommodation support for persons with disabilities.

Interested in this position?

Apply directly on the company website

Apply Now

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