Senior Technical Support Engineer Solovis is a leading portfolio management and analytics platform helping institutional investors navigate todays complex global markets with clarity and confidence. Backed by Insight Partners, were building the next chapter of growth by investing in people and product to raise the bar on quality and client outcomes. Our team is driven by a culture of disciplined execution, humility, and curiosity where AI is at the core of how we operate, innovate, and serve clients. At Solovis, youll join a tech-forward, growth-minded team that believes in learning fast, thinking big, and delivering meaningful impact for asset owners worldwide. Our companies are not the largest or flashiest, but they are among the best-run software businesses, creating value for customers and shareholders at an accelerated pace. To date, our team has built six platform companies, each culminating in multiple liquidity transactions with multi-billion-dollar valuations. The Senior Technical Support Engineer provides advanced technical support for our financial modeling and quantitative analytics software. This role sits at the intersection of technical support and consulting, requiring deep mathematical and quantitative expertise to diagnose and resolve highly complex, low-volume issues rooted in financial modeling, market data, and algorithmic logic. This role is an intentional entry point into our organization for early-career quantitative professionals. You will work alongside our quant research team and gain exposure to the full breadth of our modeling infrastructure, with a clearly defined path to grow within the organization as you develop product expertise. If you are a recent mathematics or quantitative finance graduate looking to break into the financial markets industry - and you want to do meaningful, intellectually rigorous work from day one - this role is designed for you. Key Responsibilities - Diagnose and resolve highly complex, low-volume technical issues related to financial models, quantitative methods, and market data integrations — issues that often require extended investigation to fully unwind. - Serve as the critical boundary between support and consulting: determine whether a reported issue is a product defect or a user implementation error, and guide clients accordingly. - Engage directly with clients on deeply technical matters, translating complex mathematical or computational problems into clear, actionable recommendations. - Collaborate closely with the Quantitative Research team to escalate defects, validate modeling behavior, and inform product improvements. - Partner with the Services/Consulting team when client issues require hands-on model guidance. - Document complex issue resolutions thoroughly to build institutional knowledge. - Contribute to knowledgebase content focused on quantitative methodology, model usage, and advanced configuration scenarios. Key Qualities - Intellectually curious and rigorous - you enjoy sitting with hard problems and working through them methodically. - Comfortable with ambiguity - you can investigate an issue without a clear answer in sight and remain effective throughout. - Detail-oriented with strong analytical instincts - you notice what others miss and trust data over assumptions. - Collaborative without needing to be the loudest in the room - you work well with quant researchers, engineers, and client-facing teams. - Self-directed - you manage long-running investigations independently and communicate proactively. - Resilient under pressure - you maintain composure when handling complex, high-stakes client issues. Background & Skills - Degree in Mathematics, Statistics, Financial Engineering, or a closely related quantitative field — required. - 0–2 years of professional experience; recent and upcoming graduates strongly encouraged to apply. - Hands-on experience with financial modeling through coursework, research, or internships in a quantitative or research environment. - Strong foundation in quantitative methods: statistics, probability, linear algebra, calculus, and numerical methods. - Ability to read and reason through code to isolate model behavior (Python, R, or similar preferred). - Familiarity with financial markets concepts such as pricing models, risk metrics, and market data — through academic or professional exposure. - Strong written and verbal communication skills for conveying complex technical findings to sophisticated clients.