We are looking for a PhD-level scientist to join us in developing
predictive financial models and other quantitative components of
automated trading systems. You will apply modern statistical
machine-learning methods to large, high-dimensional data sets. The work
will range from data preparation to model development to production
software implementation.
We take a rigorous approach to building trading systems, and we
actively foster a collegial, intellectual environment.
We hire on the basis of exceptional talent. If you excel in a technical
field such as statistics, mathematics, computer science, engineering,
or operations research, then we encourage you to contact us. The
following criteria, while not all requirements, illustrate the demands
of this role.
+ Background in modern statistical methods / machine learning
+ Evidence of strong mathematical abilities, e.g. publication record,
graduate coursework, or competition placement
+ Substantial programming experience and interest in software
development techniques
+ Competence in solving large-scale computing problems
+ Track record as an applied researcher
+ Demonstrable clarity of thought (not optional)
Interest in financial applications is essential, but experience in
finance is not a primary factor in our hiring.
You will architect and implement a diverse set of core infrastructures,
including new production systems, scientific-computing environments,
and modern data stores.
We seek candidates with a proven track record of writing correct,
well-designed software, solving hard problems and delivering complex
projects on time. You should preferably have experience with high
assurance, distributed, fault-tolerant systems. Experience with
functional programming as well as soft real-time, low-latency,
cache-friendly systems is a bonus.
We are looking for a PhD-level scientist to join us in developing
predictive financial models and other quantitative components of
automated trading systems. You will apply modern statistical
machine-learning methods to large, high-dimensional data sets. The work
will range from data preparation to model development to production
software implementation.
We take a rigorous approach to building trading systems, and we
actively foster a collegial, intellectual environment.
We hire on the basis of exceptional talent. If you excel in a technical
field such as statistics, mathematics, computer science, engineering,
or operations research, then we encourage you to contact us. The
following criteria, while not all requirements, illustrate the demands
of this role.
+ Background in modern statistical methods / machine learning
+ Evidence of strong mathematical abilities, e.g. publication record,
graduate coursework, or competition placement
+ Substantial programming experience and interest in software
development techniques
+ Competence in solving large-scale computing problems
+ Track record as an applied researcher
+ Demonstrable clarity of thought (not optional)
Interest in financial applications is essential, but experience in
finance is not a primary factor in our hiring.
You will architect and implement a diverse set of core infrastructures,
including new production systems, scientific-computing environments,
and modern data stores.
We seek candidates with a proven track record of writing correct,
well-designed software, solving hard problems and delivering complex
projects on time. You should preferably have experience with high
assurance, distributed, fault-tolerant systems. Experience with
functional programming as well as soft real-time, low-latency,
cache-friendly systems is a bonus.
this is a great deal for twitter, as long as their stock price does not go up. in other words, twitter is calling the top of the market for its own shares -- to the tune of 1.3B.
bezos did this to great effect with amazon in the late 90s. he did in fact correctly predict a prolonged stagnation in share price.