Quantitative Researcher

The Quantitative Researcher is responsible for designing, testing, and refining alpha-generating models that may be deployed with live capital. Researchers are expected to propose signals, rigorously stress-test assumptions, and actively participate in decisions around whether strategies should be scaled, modified, or shut down. While final capital allocation authority sits with the CIO, researchers are expected to advocate for and against their own work based on evidence.

Key Responsibilities

• Develop and evaluate quantitative strategies with an initial focus on equities and equity-linked derivatives, with expansion to other asset classes over time

• Translate economic intuition into systematic, testable hypotheses

• Conduct robustness testing designed to disconfirm ideas, not validate them

• Partner with traders to understand how live execution differs from back tests

• Recommend scaling, throttling, or termination of strategies when assumptions degrade

• Maintain clear documentation of assumptions, failure modes, and regime sensitivity

• Evaluate emerging technologies and portfolio construction techniques with potential to improve investment outcomes

Skills & Qualifications​

• Masters/PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field

• Strong knowledge of probability and statistics

• Prior experience working in a data driven research environment

• Experience with translating mathematical models and algorithms into code (Python & C++)

• Independent research experience

• Ability to manage multiple tasks and thrive in a fast-paced team environment

• Excellent analytical skills, with strong attention to detail

• Strong written and verbal communication skills

Quantitative Trader

The Quantitative Trader is responsible for live execution and real-time risk management of systematic strategies, with an initial focus on equities and equity derivatives. This role is not passive execution. Traders are expected to challenge research assumptions, influence model evolution based on live behavior, and act as the first line of defense when reality diverges from theory.

Key Responsibilities

• Execute systematic strategies with precision, initially focused on equities and related instruments

• Monitor intraday P&L, drawdowns, liquidity, and execution anomalies

• Actively push back on research assumptions when live behavior contradicts expectations

• Recommend throttling, pausing, or shutting down strategies when execution risk increases

• Provide structured feedback to researchers on slippage, fill quality, and market impact

• Participate in post-mortems with the explicit goal of improving future models​

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Skills & Qualifications​​

• Minimum 3 years of experience in an equities options trading seat with a quantitative/systematic objective

• Experience in research associated with equity products including but not limited to equity options, factor based risk modeling and other equity derivative products

• Strong quantitative skills as well as a deep understanding of python are required

• An advanced degree in a mathematically rigorous field of study

• Inspire Entrepreneurship in People

• Inspire team members through effective communication of ideas and motivate them to actively enhance productivity

• Elevate Organizational Capability

Software Developer

The Software Developer is responsible for designing, building, and maintaining the core software systems that power Solvane’s research, trading, risk management, and internal workflows. This role focuses on production-grade engineering, system reliability, and internal tooling, working closely with the AI Researcher to build, integrate, and deploy AI-driven tools for live trading and research. The role is not support-oriented; the Software Developer is expected to own systems end-to-end, make sound architectural decisions, and proactively surface risks, constraints, and failure modes as systems move from research into live operation.

Key Responsibilities

• Build and maintain core trading, research, and risk infrastructure

• Collaborate closely with the AI Researcher to design, implement, and productionize AI-driven tools for live trading and research

• Integrate AI outputs into governed, reliable, and auditable production systems

• Develop internal tools, dashboards, and APIs for strategy monitoring, P&L, and risk visibility

• Ensure systems are observable, resilient, and auditable under live conditions

• Implement logging, monitoring, alerting, and recovery mechanisms

• Optimize architecture and code for reliability, performance, and simplicity

• Document system assumptions, trade-offs, and known failure modes

Skills & Qualifications​

• 6+ years of professional software engineering experience

• Solid computer science fundamentals 

• Expert level programing skills in at least one of the following: Java, C++, Python

• Proven track record in software design and development

• Excellent analysis / problem solving skills

• Strong communication and teamwork skills

• Ability to manage multiple tasks in a demanding and dynamic environment

• Minimum of a Bachelor’s degree in Computer Science or a related STEM discipline

AI Researcher

The AI Researcher to architect and build our next-generation AI platform that transforms how we conduct investment research and execute trading strategies. You will develop cutting-edge AI agents that automate the full spectrum of investment workflows—from ingesting market data and generating trading signals to parsing financial documents and producing fundamental valuations. Your work will eliminate time-consuming analyst grunt work, enabling our team to stay lean, aggressive, and focused on high-value decision-making. This role sits at the intersection of machine learning, quantitative finance, and natural language processing, with direct impact on our ability to process information faster and execute with precision.

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Key Responsibilities

• Design and deploy machine learning models to ingest market data and generate quantitative/high-frequency trading signals with robust back testing frameworks

• Build advanced NLP systems using large language models to automatically parse, extract, and synthesize insights from large-scale financial documentation (10-Ks, earnings transcripts, research reports)

• Engineer AI agents that autonomously produce DCF valuations, comparable company analyses, and other fundamental analysis workflows traditionally performed by equity analysts

• Develop scalable, production-grade AI infrastructure and real-time data pipelines that ensure low latency, high reliability, and seamless integration with trading operations

• Create automated workflows for financial statement analysis, anomaly detection, and investment thesis generation with supporting quantitative evidence

• Stay at the forefront of AI/ML research (LLM agents, time-series forecasting, RAG, reinforcement learning) and rapidly prototype novel techniques applicable to financial markets

• Collaborate with traders and analysts to identify manual bottlenecks and translate them into automated solutions that compress time-to-insight and amplify decision-making quality

• Establish MLOps best practices including model monitoring, versioning, and continuous improvement to maintain system performance and competitive edge

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Skills & Qualifications

• 3+ years of experience developing and applying advanced deep learning, self-supervised learning, and foundation models (including LLMs) to complex, large-scale data

• Continuously evaluate where AI should not be used

• ​Excellent written and verbal communication skills, with a proactive, collaborative approach to problem-solving and navigating ambiguity

• Strong proficiency in Python and experience with modern deep learning frameworks

• Solid understanding of modern AI / ML technologies and their business applications in the investment industry