Lead Securities Quantitative Analytics Specialist

Wells Fargo Bank•Charlotte, NC

1d•Onsite

About The Position

Wells Fargo is seeking a Quantitative Software Engineer (Lead Securities Quantitative Analytics Specialist). A successful applicant will be a Python quantitative developer in the Investment Portfolio in Wells Fargo Securities, with a focus on Juniper Vasara ALM development. Vasara is the next generation risk platform for the bank. It is an ambitious, green field initiative to tackle the bank's risk computation challenges within capital markets, from ticking risk for trading desks to market risk and capital calculations such as FRTB and CCAR. Juniper Vasara is a joint venture between multiple Quant and Technology teams, and you will work as an ALM quant developer focusing on specific risk management and balance sheet strategy solutions for our portfolio management partners. Juniper Vasara is a horizontal solution designed to be use case agnostic to achieve maximum consistency and re-usability.

Requirements

5+ years of Securities Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Master's degree or higher in computer science or finance/mathematics
Experience in software development cycle and agile technologies, e.g. Git, Jira, Confluence
Excellent verbal, written, and interpersonal communication skills

Nice To Haves

4+ years of hands-on coding experience, Python and C++ are most relevant
Product and market experience in various asset classes: rates, foreign exchange, credit, and mortgages, and structured products
Quantitative analytics library software development experience in a buy-side or sell-side institution or a quant solution vendor
Hands on experience with ALM frameworks or prior experience in ALM vendor software
Strong proficiency in Python is encouraged.
Understanding of advanced language features, runtime behavior, and performance characteristics
Deep understanding of CPython internals (interpreter loop, memory model, GIL, garbage collection); experience customizing or extending the Python interpreter or standard library is a plus
Proven experience with Python interoperability and bindings to lower-level languages (e.g., C/C++, Cython, pybind11, Java)
Hands-on experience writing high-performance GPU code using Python-based DSLs (e.g., Triton, CUDA Python, JAX/XLA kernels)
Demonstrated expertise in Python performance optimization across CPU architectures using tools such as Numba, Cython, vectorization, and profiling techniques
Experience designing and developing large-scale, distributed, high-performance Python systems in production
Strong understanding of multithreading and multiprocessing in Python, including practical strategies for working with or around the GIL in real-world production environments
Experience operating Python systems under strict latency, throughput, or reliability constraints (e.g., low-latency trading systems, ML inference serving, large-scale data pipelines)
Experience interpreting and solutioning for risk
Experience in or passionate about Agentic AI

Responsibilities

Implement ALM models and logic in Python.
Integration of pricing and risk analytics in collaboration with other quant teams, providing expertise in design and implementation issues relate to ALM.
Effective communication and collaboration with Business Stakeholders, other Quant Teams, Technology Partners, and Project Management
Analyze performance, propose remedial or optimization plans, and ensure execution to enhance the new strategic valuation and risk platform for the securities businesses
Consistently deliver high-quality software and documentation in an Agile SDLC