Statistical / ML Quant Developer

Statistics / Data Science Orientated Quantitative Developer (Mid-Senior Level, NYC Hedge Fund)

Role: Agile buy-side investment team looking to partner with machine learning / statistics focused Quantitative Developer. This person will spearhead data-driven initiatives for one of the market's most significant macro portfolios. In other words: drive quantitative solutions for challenges related to macro-economic analysis. Partner directly with existing team to power the development and scaling of investment strategy.

Team: Lean, semi-systematic fixed income team. Predominantly focused on rates with coverage across areas inc. equities, commodities, emerging markets. Flat-structured approach, with significant emphasis on continuous learning, information sharing and idea generation. Despite building out some of the industry's longest-running strategies, the team consistently work to originate, research and scale novel ideas.

Platform and Technologies: Highly sophisticated platform, tools and trading engine. Technologies built, extended and supported by high-performing technology division (ex-Meta, ex-Bridgewater). Exclusive and established relationships with best-in-class data vendors. Working with both lesser-seen proprietary data in combination with public and alternative data.

Responsibilities and Requirements:

• Collaborate cross-functionally with investment team: including economists, quantitative research, senior portfolio manager.
• Innovation driven & a team player: enjoys work environment shaped by on-desk discussion and quick feedback loop.
• Strong communication in context of business-critical challenges. Understanding non-technical needs and delivering bespoke quantitative solution and iterating accordingly.
• Problem solver who thrives when tasked with making sense of highly complex datasets. (e.g. NLP and AI transformer models)
• Deep-diving into technically challenging tasks through full data R&D lifecycle: researching novel data-sets and leveraging existing ones, thinking holistically and subsequently integrating them into business-facing quantitative models and analytical reports.
• Leverage machine / deep learning models to build scalable tools in response to real-world economic environment.

Profile:

• 5-12 years of experience working across Data Science / Software Engineering / Statistical Engineering role. (Years of experience is a guideline only. Role entails significant ownership. Other factors taken into account: e.g. evidence of prior high-impact projects or PhD in relevant field).
• 3 years experience working in Python and relevant data science / statistics libraries (e.g. Pandas, NumPy, matplotlib, statsmodels).
• Evidence of well-founded understanding of macro-economic concepts through previous roles or academic background.
• Excellent academic background. Dual honors degree in Computer Science and Economics from ivy league / equivalent university is highly desired. (Operations research, physics, econometrics, statistics etc also relevant.)
• Experience with ML techniques and time-series analysis is essential. Additional NLP / DL experience highly desirable.

Applications: Accepted via LinkedIn or email: pia.robinson@thurnpartners.com