I
InnovestX
Quantitative Researcher
Skills
Google Cloud PlatformSQL QueriesPythonNumPypandasData AnalysisAIAWSAzure
6 days ago
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Important information
Contract type:
Permanent
Work mode:
Onsite
Published on:
22 October 2026
What they need
What you'll do
- Research & Analytics — Develop cross-sectional and time-series signals across markets and asset classes, translating large volumes of market data into actionable investment insights.
- Systematic Investment Strategy — Convert research into investable strategies with realistic assumptions on transaction costs, slippage, capacity, and turnover. Build and maintain the full pipeline, from back testing through to live performance monitoring.
- AI & Automation — Build AI-powered solutions and agentic research workflows that scale the team's research throughput and support cross-functional projects with firm-wide impact.
- Product Development & Innovation — Work alongside Product Managers, Data Engineers, Software Engineers, Designers to transform research outputs into production-grade features within the InnovestX platform. Own initiatives end-to-end, from initial hypothesis through production deployment and ongoing performance monitoring.
Who we’re looking for
- Bachelor's in Computer Science, Computer Engineering, Financial Engineering, Mathematics, Statistics, Physics, Economics, or a related quantitative field.
- 0-3 years experience in a quantitative, data, or research role.
- Strong Python for research and data analysis (pandas, NumPy), plus working knowledge of SQL.
- Rigorous analytical and problem-solving skills, with sound judgment on what makes a result robust.
- Ability to explain complex ideas clearly to technical and non-technical audiences.
- Demonstrated interest in financial markets, investing, and technology.
- Hands-on experience building with LLMs and Generative AI.
- Familiarity with LangChain/LangGraph, MCP, vector databases, RAG, or agentic frameworks.
- Background in quantitative investing, algorithmic trading, portfolio construction, or financial modeling.
- Exposure to Git, APIs, cloud platforms (Azure, AWS, GCP), and software engineering practices.
- Experience with Bloomberg, FactSet, LSEG/Refinitiv, Capital IQ, SEC filings, or earnings transcripts.
- CFA, FRM, or CAIA charter, or progress toward one.
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