Nascent is looking for a data-minded engineer to join their quantitative trading desk, Sovereign, to uncover, evaluate, and integrate new data sources to fuel research and trading strategies. The role involves developing pipelines, analyzing diverse datasets, and building scalable workflows for quantitative discovery.
Requirements
- Strong track record working with analytical environments like Pandas, Polars, R, Matlab, or Julia, with the ability to move quickly from prototype to production
- Proficient in Python and SQL, with experience building tools that streamline data access and exploration
- Comfortable using AI coding assistants and LLMs (e.g. Copilot, ChatGPT) to accelerate analysis and automation
- Experience working with time series data and an intuitive grasp of its quirks, challenges, and patterns
- Exposure to complex systems such as rules engines, risk infrastructure, or search platforms, and a pragmatic mindset for building in those environments
- Familiarity with tools like Docker, Linux CLI, or observability workflows (e.g. logs, memory profiling)
Responsibilities
- Proactively identify and evaluate novel data sources that could drive alpha, collaborating with traders and researchers to prioritize exploration based on signal potential
- Conduct exploratory analysis on new datasets, rapidly building intuition for structure, anomalies, and usability
- Acquire historical datasets and build automated pipelines to ensure freshness, reliability, and scalability over time
- Standardize disparate datasets into coherent schemas to support seamless downstream research and modeling
- Design and implement custom AI agents and other LLM-based tools to create reusable workflows for dataset evaluation, ingestion, and transformation
- Partner cross-functionally with engineers, quants, and business leads to develop a shared understanding of data needs and surface high-impact opportunities
- Develop strong intuitions around the structure and quality of datasets, quickly identifying gaps, inconsistencies, or anomalies that impact downstream use.
Other
- You thrive in ambiguity and less-structured environments and feel comfortable building structure and executing your own plans.
- You get energy from both starting new projects and optimizing/maintaining what you've built as well as working closely with interdisciplinary teams.
- You're naturally curious and can independently deep-dive into unfamiliar tools or topics.
- The opportunity to learn, experiment and build in an entrepreneurial environment
- Remote and distributed working environment with opportunities for in-person collaboration
