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Lead Data Scientist (Fintech / Banking)

8 hours, 39 minutes ago
United Kingdom, Denmark, Switzerland, Egypt, Saudi Arabia, United Arab Emirates
Lead
Data Scientist
Data Science and Analytics
Agile Apache Airflow AWS Azure CI/CD Feature Engineering GCP Kubeflow Machine Learning MLflow MLOps NLP Python PyTorch Scikit-learn SQL TensorFlow
Apply Now
Xenon7

Xenon7

Xenon7 provides advanced AI solutions and consultancy services, leveraging a team of highly qualified experts and a strong emphasis on research and innovation to address complex industry challenges and enhance operational efficiency.

Internet Software & Services
Founded 2014
View All Jobs 26

Description

  • Lead, mentor, and grow a team of 5–10 data scientists and ML engineers.
  • Define the data science roadmap aligned with business, product, and engineering goals.
  • Own the full lifecycle of ML models from ideation through deployment and monitoring.
  • Collaborate with cross-functional stakeholders including Product, Engineering, Risk, Compliance, and Business teams.
  • Build and optimize predictive models for credit risk, fraud detection, customer segmentation, churn prediction, and personalization.
  • Architect scalable ML pipelines using modern data platforms.
  • Conduct exploratory data analysis, feature engineering, and model validation.
  • Ensure model governance, fairness, explainability, and regulatory compliance, especially in BFSI contexts.
  • Champion agile methodologies, rapid experimentation, and iterative delivery.
  • Implement best practices for model versioning, CI/CD, and model monitoring.
  • Translate complex data insights into clear, actionable business recommendations.

Requirements

  • 8+ years of hands-on experience in Data Science, Machine Learning, or Applied AI.
  • Proven experience leading teams of 5–10 people in high-velocity environments.
  • Strong background in fintech, digital banking, payments, lending, or risk analytics.
  • Expertise in Python and SQL.
  • Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • Experience with MLOps tools such as SageMaker, MLflow, Kubeflow, or Airflow.
  • Deep understanding of statistical modeling, supervised and unsupervised learning, NLP, and time-series forecasting.
  • Experience working with large-scale data pipelines and distributed systems.
  • Strong communication skills with the ability to influence senior stakeholders.
  • High agility, ownership mindset, and a positive, collaborative attitude.
  • Preferred experience in credit scoring, fraud analytics, or regulatory-grade model development.
  • Exposure to real-time decisioning systems is preferred.
  • Prior experience in startups or high-growth fintech environments is preferred.

Benefits

  • Opportunity to lead high-impact data science initiatives in a rapidly scaling fintech environment.
  • Cross-functional ownership and autonomy.
  • Competitive compensation.
  • Performance-based rewards.
  • Collaborative, innovation-driven culture.

Interested in this position?

Apply directly on the company website

Apply Now

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