We’re looking for a hands-on Senior Data Scientist / ML Engineer to help build and deploy scalable machine learning solutions across financial products.
This is a practical, business-focused role for someone who enjoys taking models from experimentation through to production and working closely with engineering, product, and business teams to drive measurable impact.
What You’ll Do:
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Build and deploy machine learning models for real-world business problems
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Develop end-to-end ML pipelines including data preparation, training, validation, deployment, and monitoring
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Work with large and complex datasets to generate actionable insights
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Partner with engineering teams to productionize models and APIs
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Collaborate with stakeholders across product, risk, operations, and analytics
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Improve model performance, reliability, and scalability
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Contribute to MLOps, automation, and deployment best practices
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Support AI and advanced analytics initiatives across the business
Required Skills & Experience:
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6+ years of experience in Data Science, Machine Learning, or ML Engineering
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Strong Python and SQL skills
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Experience building and deploying ML models into production environments
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Strong understanding of machine learning fundamentals and model evaluation
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Experience working with cloud platforms (AWS, Azure, or GCP)
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Experience with tools/frameworks such as:
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scikit-learn
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PyTorch or TensorFlow
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Spark or Databricks
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Docker / CI-CD pipelines
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Experience building APIs or production services
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Ability to work with both technical and non-technical stakeholders
Preferred:
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Banking, fintech, or financial services experience
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Experience with customer analytics, fraud, or decisioning models
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Familiarity with MLOps and model monitoring
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Exposure to NLP, LLMs, or Generative AI use cases
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Experience with Airflow, MLflow, Kubernetes, or Hadoop ecosystems
We value people who:
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Take ownership and solve problems end-to-end
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Can balance experimentation with production delivery
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Think commercially and focus on business outcomes
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Communicate clearly and work well across teams
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Enjoy building scalable, reliable systems
Tech Environment
Python • SQL • Databricks • Spark • Docker • APIs • Cloud Platforms • MLflow • CI/CD • Power BI