WHAT MAKES US, US
Join some of the most innovative thinkers in FinTech as we lead the evolution of financial technology. If you are an innovative, curious, collaborative person who embraces challenges and wants to grow, learn and pursue outcomes with our prestigious financial clients, say Hello to SimCorp!
At its foundation, SimCorp is guided by our values — caring, customer success-driven, collaborative, curious, and courageous. Our people-centered organization focuses on skills development, relationship building, and client success. We take pride in cultivating an environment where all team members can grow, feel heard, valued, and empowered.
If you like what we’re saying, keep reading!
WHY THIS ROLE IS IMPORTANT TO US
At SimCorp, we develop technology and analytics that help some of the world’s leading financial institutions manage complex investment portfolios and make better-informed decisions.
We are looking for a Senior Financial Engineer to join our Quantitative Pricing & Risk Analytics (QPRA) team in New York.
The successful candidate will combine strong quantitative finance expertise with excellent software engineering skills and an interest in applying modern AI technologies to quantitative research and development.
You will work on models and analytics for pricing and risk across multiple asset classes, taking ideas from mathematical formulation and numerical experimentation through to robust, production-quality implementations. You will also help us explore how generative AI, coding agents, retrieval systems, and other AI-assisted workflows can improve quantitative research, model development, testing, documentation, and support.
We are looking for someone who enjoys difficult quantitative problems, writes high-quality software, communicates clearly, and is comfortable working collaboratively across financial engineering, product management, engineering, and client-facing teams.
WHAT YOU WILL BE RESPONSIBLE FOR
- Research, develop, and implement models for the pricing and risk management of financial instruments across multiple asset classes, including derivatives.
- Develop analytics using techniques such as closed-form solutions, Monte Carlo simulation, trees/lattices, numerical integration, optimization, and PDE methods.
- Develop and implement model calibration and numerical methods required for production pricing and risk systems.
- Develop methodologies for market risk, sensitivities, scenario analysis, and portfolio analytics.
- Translate quantitative models into robust, scalable, production-quality software.
- Validate models and implementations through analytical reasoning, numerical testing, benchmarking, and comparison with market or reference results.
- Investigate complex model, analytics, and client problems and determine their underlying quantitative or implementation causes.
- Collaborate with product management, engineering, and client-facing teams to translate financial requirements into quantitative solutions.
- Produce clear technical documentation, model documentation, research notes, and, where appropriate, external white papers or publications.
- Use modern AI-assisted development tools to accelerate research, coding, testing, debugging, documentation, and investigation while maintaining rigorous validation of generated results.
- Explore applications of LLMs and agentic AI to quantitative-finance workflows, including retrieval over technical knowledge, code and document analysis, automated testing, research assistance, and reusable quantitative workflows.
YOUR QUALIFICATIONS
- PhD in a highly quantitative discipline such as Mathematics, Mathematical Finance, Computational Finance, Physics, Computer Science, Statistics, or a related field. An exceptional MFE or equivalent quantitative degree will also be considered.
- Approximately 3–5+ years of relevant professional experience in quantitative finance, financial engineering, derivatives, pricing, risk, or quantitative software development.
- Strong understanding of derivatives pricing, mathematical finance, numerical methods, and/or market risk methodologies.
- Strong programming and software-engineering skills.
- Experience implementing mathematical models in production or research-quality software.
- Strong analytical and problem-solving ability, including the ability to investigate unfamiliar financial instruments or models.
- Excellent written and verbal English communication skills.
- Ability to communicate complex quantitative concepts to both technical and non-technical audiences.
Programming and technical skills
- Strong proficiency in at least one production programming language. C# and/or C++ experience is particularly relevant.
- Strong working knowledge of Python for quantitative research, prototyping, data analysis, testing, or automation.
- Solid understanding of object-oriented programming, numerical computing, algorithms, software design, version control, and automated testing.
- Experience working with large quantitative codebases or analytics libraries is advantageous.
Desired
- Strong knowledge of credit derivatives
- Practical experience using AI-assisted software-development tools, such as GitHub Copilot or comparable coding assistants, for implementation, testing, debugging, code understanding, or technical documentation.
- Familiarity with large language models (LLMs) and their strengths and limitations when applied to technical and quantitative work.
- Ability to use AI tools critically, including verifying generated code, mathematical reasoning, numerical results, and cited information rather than treating model output as authoritative.
- Experience using AI to navigate and reason over large codebases, technical documentation, research material, or other domain-specific knowledge.
- Familiarity with retrieval-augmented generation (RAG), embeddings/vector search, knowledge graphs, or related approaches for grounding AI systems in domain knowledge.
- Experience applying AI to quantitative finance, model development, model validation, financial-data analysis, or financial-software engineering.
- Familiarity with modern AI development environments and agentic coding workflows.
WHAT WE VALUE
- Quantitative depth: you want to understand why a model works, not simply run it.
- Engineering discipline: research becomes valuable when it can be implemented, tested, maintained, and trusted.
- Intellectual curiosity: you are comfortable learning unfamiliar instruments, models, technologies, and markets.
- Critical use of AI: you see AI as a powerful engineering and research tool, but understand that quantitative results require independent verification.
- Collaboration: you can work across quantitative research, software engineering, product management, and client-facing organizations.
- Clear communication: you can explain sophisticated mathematical and financial ideas without unnecessary complexity.
BENEFITS
SimCorp offers several benefits that might play a significant factor in considering whether to accept a job offer. Since SimCorp operates in 30+ offices worldwide, the benefits package may vary from country to country.
Simcorp follows a global hybrid policy, asking employees to work from the office two days each week while allowing remote work on other days.
NEXT STEPS
Please send us your application in English via our career site as soon as possible, we process incoming applications continually. Please note that only applications sent through our system will be processed. At SimCorp, we recognize that bias can unintentionally occur in the recruitment process. To uphold fairness and equal opportunities for all applicants, we kindly ask you to exclude personal data such as photo, age, or any non-professional information from your application. Thank you for aiding us in our endeavor to mitigate biases in our recruitment process. If you are interested in being a part of SimCorp but are not sure this role is suitable, submit your CV anyway. SimCorp is on an exciting growth journey, and our Talent Acquisition Team is ready to assist you discover the right role for you. The approximate time to consider your CV is three weeks.
We are eager to continually improve our talent acquisition process and make everyone’s experience positive and valuable. Therefore, during the process we will ask you to provide your feedback, which is highly appreciated.
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