Lead Data Scientist – Fintech, Banking

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Xenon Seven

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Artificial Intelligence • Enterprise

Xenon Seven is a company that specializes in providing AI and data solutions across various industries, including healthcare, financial services, consumer retail, high-tech, automotive, and energy utilities. With expertise in generative AI, decision support systems, predictive analytics, computer vision, robotics, and mechatronics, they support businesses in AI preparedness, exploration, transformation, and scalability. Xenon Seven works with a network of AI technologists and experts from over 20 institutions, focusing on solving complex problems and ensuring secure and seamless AI transitions for businesses. Their services aim to optimize AI infrastructure and performance while maintaining strict security standards.

11 - 50 employees

🤖 Artificial Intelligence

🏢 Enterprise

📋 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. • Drive end‑to‑end ownership of ML models — from ideation to deployment and monitoring. • Collaborate with cross‑functional stakeholders (Product, Engineering, Risk, Compliance, Business). • 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). • Champion agile methodologies, rapid experimentation, and iterative delivery. • Implement best practices in versioning, CI/CD for ML, and model monitoring. • Translate complex data insights into clear, actionable business recommendations.

🎯 Requirements

• 8+ years of hands‑on experience in Data Science, ML, or Applied AI. • Proven experience leading teams of 5–10 in high‑velocity environments. • Strong background in fintech, digital banking, payments, lending, or risk analytics. • Expertise in: • - Python, SQL • - ML frameworks (TensorFlow, PyTorch, Scikit‑Learn) • - Cloud platforms (AWS, GCP, Azure) • - MLOps tools (SageMaker, MLflow, Kubeflow, Airflow) • - Deep understanding of statistical modeling, supervised/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. • Experience in credit scoring, fraud analytics, or regulatory‑grade model development. • Exposure to real‑time decisioning systems. • Prior experience in startups or high‑growth fintechs.