1-1-8. Career Support

1. Quantitative Trading – LESSON 1 Welcome to the Nanodegree Program

My name is Jonathan Larkin,

and I’ve worked in quantitative finance now for

about 20 years at Investment Banks Hedge Funds and Fintech startups,

and I’m very excited to be advising Udacity on this program.

I wanted to become a quant trader,

because I was genuinely very,

very fascinated with the field.

It’s an incredibly interdisciplinary field, to be successful,

you have to draw upon

pure technical skills in areas like computer science and mathematics,

but you also have to understand markets,

understand psychology, and it needs to be able to

bring that together in a commercial result.

I really enjoy working with complex dynamic systems,

and I’ve always enjoyed that in

various endeavors and there’s nothing more complex than financial markets.

There’s always something to learn.

If I look back on my career spanning over 20 years,

I’ve seen things change in an extraordinary way.

When I first started in the field,

there was no algorithmic trading,

now everything is completely automated.

You’ll find quants working across the entire financial industry these days.

Most people associate the job of a quant with very well known quantitative hedge funds,

and it is certainly true that quants work in that type of organization,

but quants also work in commercial banks, proprietary trading firms,

asset management firms, data vendor firms,

and they also work across functions.

You’ll find quants working in many aspects of an investment organization.

You’ll find quants in the research function,

those are quants looking for predictive signals and

data that can be applied downstream to a portfolio,

you’ll find quants working in risk management trying to

predict the risk of a particular portfolio or the risk firm wide.

You’ll find quants working in

portfolio construction combining the signals and models produced by other quants,

you’ll also find quants working in data vendors,

and data vendors who are preparing

unstructured data than to sell to the financial industry.

The curriculum in this program is specifically designed

to be very very practical and very applicable to the quant trading process,

both in a classical sense,

but also in the analysis of new data and then the

application of machine learning and artificial intelligence techniques.

As such, students coming out of this program should

be very attractive candidates to go into quant-trading rules.

The traditional way to become a quant is to get a stem based degree at a top university.

Go to your Career Center and they’ll introduce you to a host of financial firms,

you interview, you get an offer,

you join an analyst program and

then you get training and mentorship and you take it from there.

Quant firms have traditionally hired from say the top 20 universities.

The problem with that is say for circumstantial reasons,

the top talent in the world may not be at those 20 universities.

Given that quant firms are in a war for talent,

and their success is dependent on

new innovative and diverse ideas coming from their employee base,

it really behooves them to cast the widest possible net.

The Udacity nanodegree, I’m confident will be

a strong feeder for this next generation of quant.