Summary

OXBO are working with a multi-billion dollar asset management firm operating across the USA, UK and UAE. The role supports the the front office business in a team consisting of software engineers, quants, and data scientists that provide business solutions for the cross-asset investment team.

The business remit focuses on the delivery of end-to-end tools for data analytics, investment management, AI and cross-asset tooling.

The role is based in NYC and will work on a hybrid basis.

Responsibilities

• Develop Analytics & Tools: Build and maintain analytics, models, and calculation engines that support investment decision-making, portfolio monitoring, risk management, and performance reporting. 
• Design Data Pipelines & Platforms: Engineer scalable pipelines, data models, and platform tools (using Python, PySpark, SQL, and BI/web frameworks) to transform complex financial datasets into reliable, production-ready solutions. 
• Create User-Facing Solutions: Deliver interactive dashboards, APIs, and lightweight web applications that enable portfolio managers, quants, and other stakeholders to explore data, run scenarios, and generate custom insights. 
• Partner with Investment Teams: Work directly with portfolio managers and analysts across asset classes to capture requirements, validate prototypes, and translate business needs into technical deliverables. We also lead the onboarding of new investment teams in terms of the data, technology, and analytics they need to get started trading. 
• Collaborate Cross-Functionally: Integrate with Data Engineering/Ops, Market Data, Data Governance, Application Support, Front Office Systems, and other technology teams to ensure solutions are deployed, monitored, and maintained with scalability, reliability, and security in mind. 

Experience Required

• Degree in a technical or quantitative discipline (e.g., Computer Science, Mathematics, Statistics, Financial Engineering) 
• Experience ​(roughly 3-5 years) as a software engineer, preferably in a front-office facing role within the financial industry.​ 
• Strong proficiency in at least one programming language 
• Experience with the Python data analytics ecosystem (Pandas, matplotlib, plotly, Jupyter) 
• Experience in at least one asset class such as equities, credit, convertible bonds, or structured products, or private markets 
• Expertise in SQL and relational database design; familiarity with big-data frameworks (Spark, Dask, Databricks, Snowflake). 
• Familiarity with BI platforms (e.g., Sigma, Tableau, Power BI) and/or web application frameworks (e.g., Dash, Streamlit, Django). 
• Excellent communication skills and demonstrated ability to translate business requirements into technical solutions and communicate insights clearly to both technical and non-technical stakeholders.  
• Strong problem-solving and organizational skills, with the ability to learn fast and adapt quickly across various asset classes and investment strategies.   
• Ability to work independently as well as in a small, collaborative team.  
• Strong interpersonal skills, fun/easy to work with, fostering a collaborative and positive work environment.