Data Scientist

Job Description:

Deep Light AI is a specialist AI and data consultancy dedicated to transforming the regional corporate landscape through bespoke, high-impact intelligent systems. We combine deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex corporate operations.

With particular depth in the financial services and banking sectors, we help our clients bridge the gap between complex data and actionable business strategy. We dont believe in "off-the-shelf" fixes—we build secure, scalable solutions that integrate seamlessly into enterprise architectures.

We are seeking a Data Scientist with deep banking domain awareness to design, develop, and deploy robust statistical models and data-driven solutions for our premier regional clients.

In this role, you will work across Treasury, Wholesale Banking, and Corporate Lending divisions to build high-impact risk models, portfolio optimization frameworks, and regulatory capital solutions. Operating at the intersection of quantitative science and practical banking operations, you will translate complex financial challenges into precise, production-ready statistical solutions.

• Build Advanced Risk Models:
  Design and implement statistical risk models for corporate lending, wholesale banking, liquidity management, and treasury operations—including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) architectures.
• Optimize Capital & Returns:
  Build analytical modules for Risk-Adjusted Return on Capital (RAROC) and Risk-Adjusted Capital (RAC) optimization frameworks to help business lines maximize risk-adjusted returns.
• Ensure Regulatory Alignment:
  Apply Basel requirements (Basel III/IV), stress testing frameworks, and regulatory capital rules to guarantee all model designs conform to global and regional banking standards.
• Drive Engineering Excellence:
  Write clean, modular, and well-documented Python code while actively participating in peer code reviews to maintain high scientific and software engineering standards across engagement squads.
• Collaborate & Communicate:
  Partner closely with client risk officers, business analysts, and technical leads to decompose complex requirements, present quantitative findings, and defend model methodologies.

As an AI consultancy, our greatest asset is the expertise of our people.
While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight.
We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills.
You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders.
If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in.

• Hands‑on experience developing statistical risk models or quantitative frameworks within corporate banking, wholesale banking, or treasury environments.
• A strong theoretical and practical understanding of the quantitative, mathematical, and probabilistic concepts underlying ML and statistical tools—going beyond high-level library calls to understand the science behind them.
• Strong proficiency in Python and its scientific computing ecosystem (Num Py, Sci Py, Pandas, Scikit-learn, Stats models, PyTorch/Tensor Flow).
• Solid working knowledge of the Basel III/IV framework, regulatory capital calculations, and…