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Forward Deployed Research Analyst - Equities - eFinancialCareers

eFinancialCareersNew York, NY🇺🇸United StatesPosted Sep 30, 2026

Quick Overview

Seniority
Mid Senior
Employment type
Full Time
Work mode
On Site
Location
New York, NY, United States
Posted
Yesterday
Python

Job Description

Forward Deployed Research Analyst - Equities

About The Firm

The firm is building an AI platform for hedge funds and asset managers and deploys software and custom workflows that make funds AI-native — connecting their data, encoding their expertise into agents and skills, and automating their highest-value workflows.

The team combines engineers from top institutions across finance (Citadel, Goldman Sachs, Millennium, D.E. Shaw, Two Sigma, and Bridgewater) and technology (leading data and AI startups) with forward-deployed specialists who embed directly with clients to automate real workflows.

Overview

The firm is building a small, elite team of Applied AI Analysts, seasoned finance practitioners from fundamental research, data science, and portfolio and risk management, who will work with clients to understand their workflows and help them fundamentally transform them with the firm's platform. This is a finance role at the frontier of AI adoption.

Responsibilities

  1. Embed with clients and drive AI-led workflow transformation. Work on-site with PMs and research analysts to understand how they work today, identify high leverage opportunities for automation and augmentation, and build production grade AI workflows that transform their processes.
  2. Translate client workflows into skills, agents, and connectors. Partner with the engineering team to convert new data connectors, skills, and agents. Serve as the bridge between "how investment teams think" and "how the platform is built", and the domain fluency is what makes that translation meaningful and precise.
  3. Contribute to the product feedback loop. Be a daily power user of the platform and bring structured, actionable feedback to the product team for new features.
  4. Build the firm's knowledge base for your domain. Contribute to the firm's skill and agent library of best-in-class research, risk, operations, data science, and technology best practices. These skills are designed to work collectively as a single knowledge base for AI to connect technology, data, research, risk, and trading into a single platform.

Requirements

  1. 3 -​ 7 years of experience in a core equity research function at a top tier hedge fund,​ asset manager,​ sell side research,​ RMS vendor platform,​ or institutional investment fund
  2. Multiple hands-​on projects building with AI (e.​g.​,​ GitHub repository of skills built for research,​ various side projects,​ and other demonstrated practical AI interests) while using Python
  3. Avid user of AI tools (genuine integration into workflows vs experimentation) and have strong views on what works,​ what breaks,​ and where the leverage is
  4. Hands-​on experience leveraging financial data vendors (e.​g.​,​ Bloomberg,​ Visible Alpha,​ FactSet,​ PitchBook,​ CapIQ,​ or similar)
  5. Ability to build trust quickly,​ ask the right questions,​ and navigate unstructured conversations with senior investors and C-​suite execs at top hedge funds

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