Lead Data Scientist (Fintech / Banking)

Leadership & Strategy

• 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).

Technical Execution

• 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).

Operational Excellence

• 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.

We are seeking a Lead Data Scientist (Fintech / Banking) with 8+ years of experience to drive advanced analytics, machine learning initiatives, and data-driven decision-making across our fintech/banking product ecosystem. The ideal candidate has a strong track record of leading high-performing teams (5-10 members), delivering scalable ML solutions, and operating with high agility in fast-paced environments., * 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.

Preferred Qualifications

• 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.

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

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