Python Developer (Risk)

at  Luxoft

PROJECT DESCRIPTION

Luxoft’s client, a global commodity trader, are embarking on a significant risk application modernization programme, streamlining their architecture, remediating legacy infrastructure issues and providing a new scalable platform for business growth.
We are seeking an experienced senior Python developer with a strong background in capital markets risk to join our growing team

SKILLS

Must have
Technical Skills:
5+ years of experience in Python development, with a focus on high-performance applications in capital markets or financial risk domains.
Proficiency in object-oriented programming and familiarity with libraries such as NumPy, Pandas, and SQLAlchemy.
Experience with distributed systems, microservices, and cloud-based architectures (e.g., AWS, Azure) is a plus.
Strong experience with databases (SQL and NoSQL) and handling large datasets.
Domain Expertise:
Knowledge of risk management in capital markets, particularly in market, credit, and liquidity risk.
Understanding of financial products, pricing models, and trading systems.
Soft Skills:
Excellent problem-solving skills with a proactive approach to identifying and mitigating risk.
Strong communication skills, capable of translating technical language into business needs.
Leadership skills with the ability to mentor team members and manage cross-functional collaborations.
Nice to have
Familiarity with risk management frameworks and regulatory requirements (Basel III, FRTB, etc.).
AWS Certification (AWS Certified DevOps Engineer, AWS Certified Solutions Architect, etc.).

Design and Development:
Lead the design, development, and implementation of scalable, high-performance Python-based applications for risk analysis and reporting.
Collaborate with quants, risk analysts, and other stakeholders to translate complex risk requirements into robust technical solutions.
Optimize and enhance existing Python codebases, ensuring they meet the demands of real-time risk calculations and regulatory requirements.
Data Integration:
Work with large, complex datasets from various sources including market data feeds, trading systems, and internal risk systems.
Build data pipelines and ETL processes to ensure accurate and timely risk data aggregation and reporting.
Automation & Monitoring:
Automate risk reporting processes to ensure real-time visibility and compliance with regulatory standards (e.g., Basel, FRTB).
Design and implement monitoring tools to track system performance and proactively mitigate potential risks.
Collaboration & Leadership:
Act as a technical mentor for junior developers, sharing best practices for Python development and capital markets risk knowledge.
Collaborate with cross-functional teams, including product managers, quants, and IT operations, to ensure solutions are delivered on time and meet business objectives.