Lead Data Scientist (Fintech / Banking)

About us :

Where elite tech talent meets world-class opportunities!

At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today’s most complex challenges.

About the Client :

Join one of Egypt’s premier financial institutions, renowned for its extensive suite of banking services, including Institutional Banking, Personal Banking, and Islamic Banking. With a global presence through over 50 branches and correspondents, we serve a diverse and dynamic clientele. As we embark on a groundbreaking digital transformation journey, we are committed to leveraging the latest technologies to establish a state-of-the-art data architecture that will redefine our performance and service delivery.

Requirements

Role Overview

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.

Key Responsibilities

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.

Required Skills & Experience

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.

What We Offer

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.