About Longaeva Partners
Longaeva: Pronounced “long-AY-vuh”, our name is rooted in meaning! We are named after one of the oldest and most resilient living species, the longaeva pine. It represents longevity, adaptability, and persistence. It thrives in extreme conditions and has adapted for thousands of years in harsh environments. We hope to do the same, delivering positive, risk-adjusted returns to our investors in harsh and varied market conditions. We are a New York based hedge fund with a global investment mandate focusing on long duration investing across long/short public equities and late-stage private deals. Peter Goodwin is our founder and CIO, bringing almost 20 years of investing experience across the healthcare, consumer and TMT sectors. We are a high conviction, ideas driven firm built on a foundation of high performing product specialists and an intense commitment to primary research and data.
Role Overview
Longaeva is adding an associate to join the proprietary research team to accelerate adoption of generative AI products across investment strategies. In this role, you will embed directly with the proprietary research and investment teams to build solutions that impact investment decisions. We are seeking a capable, technicalcandidate—someone able to do hands-on research product development, web scraping, and LLM/AI-powered synthesis of qualitative and quantitative data. The ideal candidate blends scrappy coding, data/information aggregation, and a strong product intuition, with a proven ability to ship projects fast and independently. You will translate our AI capabilities into actionable insights by rapidly prototyping agentic workflows, building novel research products, and driving adoption of in-house tools.
Key Responsibilities
- Drive Adoption: Embed with research and investment teams to maximize the value derived from in-house generative AI and tooling.
- Innovate: Continuously evaluate research needs to improve investment decision making by creating research products that leverage proprietary data and LLMs.
- Partner Closely: Translate and productize research and investment team ideas into concrete deliverables.
- Hands-On Product Development: Build and deploy research products, web scraping pipelines, and LLM/AI-powered synthesis tools and products.
- Scrappy Automation: Rapidly prototype and automate data aggregation and analysis workflows, plugging APIs and AI into investment research processes.
- Maintain Edge: Track emerging LLM techniques and machine learning methods, pilot promising ideas, and feed proven wins back into the investment process.
Qualifications
Education
- Degree in Data Science, Computer Science, Statistics, Mathematics, or equivalent work experience.
- Academic training in computer science, statistics, and data science techniques (including machine learning methods) is required.
- Preference for candidates with academic training in generative AI techniques.
Experience
- At least 3 years of experience in roles that involve scoping, developing, and deploying LLM-based and data solutions. Candidates must have demonstrable experience building LLM-based applications.
Technical Skills
- Proficient in Python for data manipulation, statistical modeling, and machine learning, along with SQL skills for database querying.
- Experience integrating LLMs and AI models into production workflows is a must.
- Familiarity with various LLM models, including those from OpenAI, Google, and Anthropic.
- Experience with web scraping, API integration, and rapid prototyping of automation tools.
Soft Skills
- Strong problem-solving and analytical skills.
- Excellent communication and interpersonal skills.
- Ability to work independently and as part of a team.
- Demonstrated ability to manage multiple projects and meet deadlines.
- Product intuition and a bias for action—able to own product vision, aggregate and analyze unique information, and deliver actionable deliverables that will generate investment insights.
