Artificial Intelligence (AI), Communication Skills, Data Analysis, Data Visualization, Detail Oriented, Embedded Systems, Git, GitHub, Multitasking, Problem Solving Skills, Programming Tools, Proof of Concept, Python Programming/Scripting Language, Risk, Risk Analysis, Source Code/Configuration Management (SCM), Stock Market, Technical Leadership, Time Series Analysis, User Experience Design (UXD), User Interface/Experience (UI/UX)
Summary:
- Location: Boston, MA
- Work Mode: Hybrid
Responsibilities:
- Serve as the technical lead embedded within the Risk team.
- Drive design and implementation of small-scale applications and proof of concepts to improve risk analysis, develop AI-enabled workflows, and enhance reporting systems and processes.
- Work closely with risk analysts and investment teams to build robust systems and tools that power risk infrastructure, analytics, and decision-ready reporting.
- Design systems, rapidly iterate over them, and deliver them across the finish line.
Requirements:
- Excellent problem-solving skills with the ability to think critically and independently.
- Effective communication skills to articulate complex ideas to both technical and non-technical stakeholders.
- Strong attention to detail and ability to manage multiple tasks in a fast-paced environment.
- Full-stack development knowledge with a minimum of 5 years of professional experience programming in Python.
- Experience with key Python Libraries (pandas, NumPy).
- Experience in front-end development and user experience (UX) design.
- Experience using Version Control (Git).
- Experience using Agentic Programming tools (Github Copilot, Claude).
- Proven ability to design, build, and scale application systems in data-rich environments.
- Strong SQL skills.
- Solid understanding of financial markets and multi-asset investment risk domain.
- Practical experience in developing and maintaining models, tools, and reports.
Preferred Skills:
- Experience with Pythonic front-end and data visualization libraries (e.g., Plotly, Dash).
- Familiarity with financial data platforms (such as Bloomberg, FactSet, Aladdin, eFront, Moodys).
- Experience with statistical and time-series data analysis using pythonic libraries (such as Scikit-Learn, SciPy, cvxpy).
A
Axelon Services Corporation