Founding Head of Quantitative Research

Compensation: 5.0% – 10.0%

Senior Quantitative Research Scientist — Founding Team

Company: Echo Financial Systems, Inc. Location: Remote (United States) Experience: 8–15+ years preferred Education: PhD in a quantitative discipline strongly preferred Compensation: Founding equity opportunity; cash compensation and timing to be discussed transparently based on funding and commitment

About Echo

Echo Financial Systems is an early-stage financial technology company building an AI-powered platform for institutional financial research, analytics, and quantitative modeling.

Our platform integrates financial statement data, market information, macroeconomic indicators, and artificial intelligence to automate sophisticated investment research and financial modeling.

We are developing an extensive financial-data ontology, automated equity forecasting models, and quantitative credit-risk analytics.

Our founding team brings experience in institutional finance, financial technology, software architecture, and enterprise product development.

The Opportunity

We are seeking an exceptional, experienced quantitative researcher to help establish Echo's quantitative research architecture.

This is not an entry-level research position or a conventional data science role. We are looking for someone who has spent years developing, testing, and implementing sophisticated quantitative models in a professional environment.

The ideal candidate combines the mathematical depth of a research scientist with the practical experience of someone who has delivered working analytical systems.

You will work directly with the founding team and have substantial influence over Echo's modeling methodology and product development.

Responsibilities

Design and implement quantitative forecasting models for corporate earnings, financial statements, and credit risk.

Apply econometrics, time-series analysis, regression, machine learning, and statistical inference to large financial datasets.

Develop sector-specific financial models using historical fundamentals, macroeconomic drivers, and market indicators.

Identify statistically meaningful relationships across financial variables while controlling for overfitting and model instability.

Construct rigorous model-validation, backtesting, and out-of-sample testing frameworks.

Develop proprietary quantitative methodologies that can be integrated into Echo's AI-powered modeling platform.

Collaborate with the CEO, CTO, and product leadership to translate quantitative research into production-ready software.

Qualifications

Required:

Significant professional experience developing quantitative models in asset management, investment banking, financial technology, economic research, or a closely related field.

Advanced expertise in econometrics, statistics, financial mathematics, or machine learning.

Strong Python programming skills and experience working with large financial datasets.

Demonstrated ability to take quantitative models from research through implementation and validation.

Independent research judgment and the ability to solve difficult, open-ended modeling problems.

Strongly preferred:

PhD in Economics, Econometrics, Statistics, Mathematics, Physics, Financial Engineering, or a related quantitative field.

Eight or more years of relevant professional experience.

Experience with equity forecasting, credit risk, fixed-income analytics, macroeconomic forecasting, or quantitative investment strategies.

Experience developing original quantitative research or proprietary financial models.

Familiarity with financial statements, accounting relationships, and institutional investment workflows.

Who We're Looking For

We value exceptional ability over conventional credentials.

We are particularly interested in someone who has demonstrated an unusual capacity to identify quantitative relationships, develop original methodologies, and solve difficult financial modeling problems.

We are not looking for someone who simply knows how to run regressions or train machine-learning models.

We want a researcher who understands why a model works, when it fails, and how to improve it.

Why Join Echo?

This is an opportunity to help build the quantitative foundation of a financial technology company from an early stage.

Rather than maintaining a narrow component of an established system, you would help design the analytical architecture that could underpin an entire institutional research and modeling platform.

The role offers significant technical ownership, direct involvement in strategic decisions, and the opportunity to participate in the company's long-term success through equity.

Echo is an early-stage venture. Funding-stage risks, current resources, and compensation arrangements will be discussed openly with prospective candidates.

How to Apply

Please submit your résumé or CV along with a brief description of the most sophisticated quantitative model you have personally developed.

We are especially interested in understanding the problem you solved, the methodology you selected, how you validated it, and whether it was deployed in a professional environment.

Website: https://echoequityresearch.com