YC W14 Fintech company is hiring Machine Learning experts
We are a YC W14 company founded by a Google software engineer and a Morgan Stanley quant trader.

We are applying machine learning, software engineering and rigorous scientific investigation to revamp the lending and securitization space. This is one of finance’s least sexy areas, but is a multi-trillion dollar market- and it’s where the financial crisis started. Bad technology was a major cause, and even after 5 years, no one has fixed it.

Now we’ve found a novel way for a startup to break into the space. We just raised a multimillion dollar seed round from top tier investors including major VCs, Max Levchin, SV Angel and Two Sigma.

We are a full-stack startup, not just another vendor; we make tools so that we can use them. We’re only 8 months old, but already close to being profitable.

Our problems are very technical: we are creating unique ML algorithms, or implementing versions that have never been used in industry before. We work with (or want to work with) approaches that span everything from traditional models like logistic regression, to SVMs, tree models and boosting, amongst many others.

We are munging data from a variety of sources, and applying advanced feature selection and engineering, as well as dimensionality reduction techniques.

THE JOBS

We are looking for full-time employees who will make foundational contributions as part of our machine learning team, which includes both founders.

Obviously, we are looking for smart, determined, hardworking individuals. But most importantly, we are seeking a self-starter who wants a challenge. There are plenty of opportunities available as junior members of established teams where you can coast. This job is NOT that. As an early-stage employee, your role will evolve quickly. You can take on what interests you, while also focusing on your core strengths.

MACHINE LEARNING RESEARCHER

What you bring to the table:

* You share our ideal of pursuit of knowledge, but disdain the not uncommon backbiting and tenure-focus of a traditional academic department

* We’re not just applying algorithms from existing libraries, we want a machine learning savant who understands our business problems, and builds novel ML algorithms that answer the questions we’re asking.

* Ph.D. level research background or industry equivalent, both devising novel algorithms and applying them to real world data.

* Extreme familiarity with supervised learning algorithms is a must.

* Knowledge of customized loss functions, imbalanced data, feature selection, and statistical decision theory is a plus

* Knowledge of quantitative finance is cool – but in no way a requirement.

What you’ll do:

* The market is our lab. You’ll investigate data, construct a hypothesis, and instead of writing a paper, actually apply your ideas and make money!

* We’re exploring ideas from across computer science and statistics, including supervised learning, natural language processing, imbalanced data and anomaly detection, deep learning, time series, feature extraction and selection, and many, many other areas.

* We are, strangely enough, very interested in ideas from biostatistics, survival analysis and epidemiology, so applied experience (or even interest) in these areas would be cool.

MACHINE LEARNING SOFTWARE ENGINEER

What you bring to the table:

* Professional experience applying machine learning techniques and building production ML systems. You should know your decision trees and SVMs, and be ready to learn a lot more!

* Coding skill in Python, C++ or similar. We currently use Python, but welcome developers of any background, as long as you can pick up Python.

* We value correctness, maintainability, elegance, and testability of code. We want to do things the right way over just getting things ‘done’. We’re strict about our code style and quality so that you don’t have to spend your time tracking down other peoples’ bugs.

* Experience in functional programming languages such as Clojure or OCaml would be a plus.

* Knowledge of quantitative finance is cool – but in no way a requirement.

What you’ll do

* Participate in cutting edge research in artificial intelligence and machine learning applications.

* Develop and implement solutions for real world, large-scale problems.

* We’re exploring ideas from across computer science and statistics, including supervised learning, natural language processing, imbalanced data and anomaly detection, deep learning and time varying systems.

What we offer

* As an early employee, you get to shape the company culture and make foundational contributions to the code base.

* Market rate salary and generous equity package

* Standard Benefits - Medical and dental insurance.

* Flexible hours and open vacation policy

This work is not for everyone, but if you’re interested, and think you might be qualified, email us at yc.fintech@gmail.com to learn more. We are located in San Francisco, CA