For Professional Investors

From Research to Implementation

Three ways to turn academic research into investment edge—from a single call with the author to a full production system.

Vetted talentScoped projectsBuilt for investment teams

Currently in private beta. We're onboarding select funds.

The Problem

Great Research. No Way to Implement It.

You found a paper that could give you an edge. Maybe it's a new factor, a signal, or an approach to portfolio construction. But turning it into something usable requires skills your team doesn't have—or doesn't have time for.

And sometimes you're not even sure if a paper is worth implementing yet.

Finding talent is hard.

Upwork is a mess. Recruiters don't understand quant finance. Your network is tapped out.

Scoping is harder.

You're not sure what you need—a PhD, a data engineer, a full dev shop? How long should it take? What should it cost?

The stakes are high.

A bad hire wastes months. Sensitive IP is at risk. You need someone who gets finance.

You shouldn't need to become a recruiting expert to get a project done.

Three Tiers

Choose Your Level of Engagement

Start with a call, validate with a sprint, or go straight to implementation. Each tier builds on the last— scale up when you're ready.

1

Expert Call

Ask the Author

$500–800/hour· 60 minutes

Talk directly to the academic author of a paper or a subject-matter expert. Understand methodology, limitations, and practical applicability before deciding to implement.

What you get:

  • 60-minute call with author or expert
  • Deep dive into methodology & limitations
  • Practical applicability assessment
  • No compliance risk (published research only)

Ideal for: Validating an idea before committing resources

2

Research Sprint

Validate Before You Build

$5,000–15,000· 2–4 weeks

A focused engagement with an academic or quant researcher to validate whether a paper's findings hold up before committing to full implementation.

What you get:

  • Literature review
  • Methodology validation
  • Replication of paper results
  • Feasibility assessment
  • Written report with findings

Ideal for: Rigorous validation with clear deliverables

3

Implementation

From Research to Production

$20,000–100,000+· Varies by scope

Full build of a production system—data pipelines, backtesting frameworks, dashboards, and tools your team can use daily.

What you get:

  • Production-ready system
  • Data pipelines & infrastructure
  • Backtesting frameworks
  • Dashboards & internal tools
  • Documentation & handoff

Ideal for: Turning validated research into working systems

How It Works

Simple Process, Any Tier

Whether you need a quick call or a full implementation, the process is the same. We handle the hard part so you can focus on the work.

1

Tell Us What You Need

Start with a free scoping call. Tell us about your project—we'll help you figure out which tier makes sense and what skills you need.

2

Get Matched

We introduce you to 1-3 vetted experts who've done similar work—academics, engineers, or dev shops depending on your needs.

3

You Choose

Interview the candidates, pick the best fit, negotiate directly. We're here if you need help evaluating.

4

Work Directly

We step back once the match is made. You work directly with your expert—no layers, no overhead, no interference.

The Talent

Specialists, Not Generalists

We curate talent specifically for investment teams. Everyone in our network has either worked in finance or has deep experience serving financial clients.

Academics power our Expert Calls and Research Sprints. Engineers and dev shops handle Implementation.

Academic Researchers

PhDs and postdocs who can replicate papers, validate methodologies, or conduct original research.

Ideal for: Factor research, backtesting frameworks, literature reviews.

Tiers: Expert Calls & Research Sprints

Quant Engineers

Engineers who speak both Python and finance. They can build data pipelines, implement models, and deploy to production.

Ideal for: Signal generation, portfolio optimization, execution systems.

Tiers: Research Sprints & Implementation

Dev Shops

Small agencies with track records serving hedge funds and asset managers. Full-stack capability for larger builds.

Ideal for: Dashboards, internal tools, end-to-end systems.

Tiers: Implementation

ML/AI Specialists

Machine learning engineers experienced with financial data—NLP for filings, alternative data processing, predictive models.

Ideal for: Earnings call analysis, sentiment extraction, forecasting.

Tiers: Research Sprints & Implementation

Use Cases

Real Requests, Real Projects

Here's what investment teams actually ask us for at each tier.

Expert Call

  • "I read a paper on momentum factors—can I talk to the author to understand the methodology?"
  • "We're considering a new approach to portfolio construction. Can we get 60 minutes with someone who's published in this area?"
  • "Before we invest in building this, I want to understand the limitations the author didn't put in the abstract."

Research Sprint

  • "We want someone to replicate this paper's results on our universe before we build anything."
  • "Can you do a literature review on factor timing strategies and tell us what actually works?"
  • "We have a thesis about earnings call sentiment—validate it rigorously before we commit engineering resources."

Implementation

  • "We need a production system that scores earnings calls for sentiment daily."
  • "Build us a backtesting framework that can handle our alternative data sources."
  • "Create a dashboard that automates our analysts' repetitive workflow."

Not sure which tier fits your needs? Start with a free scoping call—we'll help you figure it out.

Why Academic Signal

Built for How Investment Teams Work

Finance-Native Talent

Everyone in our network understands finance. No explaining what a 13F is or why latency matters.

We Help You Scope

Not sure what you need? We'll help you figure it out before you talk to anyone. Free, no obligation.

Vetted & Curated

We don't dump 50 profiles on you. You get 1-3 qualified matches who've done similar work.

IP Protection

All providers sign NDAs. We work with funds who take confidentiality seriously—and so do we.

Matchmaker, Not Middleman

We make the introduction and step back. You work directly with your provider—no layers, no overhead, no interference.

Start Small, Scale Up

Begin with a call to validate an idea, expand to a sprint for rigorous testing, then build a full system if the research holds up.

FAQ

Frequently Asked Questions

Not Sure Which Tier You Need?

Start with a free scoping call. Tell us about your project and we'll recommend the right tier and match you with vetted experts.

Questions? Email us at hi@academicsignal.com