Top Tech Jobs & Startup Jobs

Build and support internal web applications, data workflows, and AI-assisted tooling. Responsibilities include Python and SQL development, frontend changes, performance optimization, data-quality investigation, system integrations, LLM tool interfaces, user support, account provisioning, deployments, monitoring, documentation, development environments, and automated testing.

Manages the trade lifecycle for Total Return Swaps and other asset classes, including trade bookings, swap resets, corporate actions, break resolution, and daily transaction, position, and cash reconciliations in Geneva. Partners with trading, accounting, technology, risk, counterparties, and global operations teams to resolve discrepancies, improve workflows, reduce operational risk, and support effective policies and procedures.

Evaluates technology organization effectiveness across delivery, reliability, efficiency, unit economics, and AI adoption. Owns engineering intelligence metrics, analyzes cloud, AI, and market-data spending, identifies inefficiencies, quantifies opportunities, and drives remediation. Builds AI-enabled data pipelines and automation, conducts benchmarking, develops actionable recommendations, and partners with technology leaders and engineers to implement measurable improvements. Presents concise, data-driven findings with clear ownership and expected business impact.

Source and evaluate traditional and alternative datasets for quantitative investment teams. Manage data vendor relationships, pricing, contracts, renewals, licensing, compliance, budgets, and usage tracking. Coordinate dataset onboarding with Technology and Data Engineering, while ensuring data quality, documentation, metadata, and governance standards. Partner with portfolio managers, researchers, quants, Legal, Compliance, and Procurement to translate investment needs into effective data acquisition and integration strategies.

As a Quantitative Research Analyst, you will develop models, conduct complex data analysis, and work with stakeholders to optimize investment strategies.

Design, build, and maintain systems to calculate and manage margin, financing interest, and funding costs. Develop scalable near-real-time trade processing and portfolio optimization services. Collaborate with engineers, researchers, portfolio finance and traders to improve performance, resilience, and data access patterns while owning Treasury systems and workflows.

A 10-week platform internship supporting teams such as Data, Finance, Operations, Risk, Technology, Treasury, HR, Marketing, and Business Development. Interns contribute to strategic projects, automate processes and workflows, build dashboards and tools, improve operational efficiency, use AI tools, participate in a trading simulation, and present work to senior leaders.

Ten-week technology internship at a multi-strategy hedge fund. Interns join a technology team and contribute to data ingestion, high-performance processing, modeling, portfolio and risk management, live execution, and post-trade analysis. The program includes strategic projects, trading simulations, mentorship, professional development, and presentations to senior leaders. Candidates should have a STEM background, programming experience, machine learning and AI knowledge, strong analytical and communication skills, and interest in financial services.

Ten-week investment internship supporting a portfolio management team at a multi-strategy hedge fund. Responsibilities include identifying and evaluating data-driven investment insights, contributing to strategic projects, participating in a trading simulation, and presenting work to senior leaders. Interns receive mentorship, exposure to investment and platform teams, professional development, and networking opportunities.

Design, operate, and improve Verition's global network platform across datacenters, cloud, and internet edge. Build high-performance datacenter fabrics (EVPN/VXLAN, BGP, leaf-spine), WAN and market connectivity, security, observability, and low-latency optimizations. Automate provisioning, configuration, validation, and monitoring using Python, APIs, Git, and IaC tools. Partner with cross-functional teams, provide production support/on-call, and drive platform reliability, performance, and scalability improvements.