Mathematical Scientist - San Jose, United States - Pit Technologies Inc.

Description

Pit.
AI Technologies is taking on one of the most exciting challenges of our time, namely solving intelligence, in one of the most competitive industries ever, investment management

The team enjoys the duality of solving humongous research and engineering problems, while remaining focused on very concrete shorter-term breakthroughs.

We believe in excellence, humility, trust and inclusion, and every team member has a veto power on who we hire.

We are backed by Y Combinator, legendary Renaissance Technologies and First Round Capital co-founder Howard Morgan, and prominent tech VCs David Lee & Zal Bilimoria, to name but a few.

Pit.
AI Technologies is hiring a Mathematical Scientist.

You'll be at the core of our effort to solve intelligence for investment management, and as such, you'll work very closely with the CEO/CTO to improve our current generation of AI-Quants.

This role is an
_in-house mathematician_ role.

As such, you'll be involved in formulating fundamental questions arising as part of the investment process as mathematical problems consistent with our research philosophy, and you'll be responsible for solving those mathematical problems.

This role is central to our research efforts, and your output is expected to have a critical impact on our bottom line, both in the short term and in the long term.

Pit.
AI Technologies supports publications of methodological findings to top machine learning venues.


Requirements:

• Ph.

D.

/ Post Doc in Maths from a top university or research group, with an emphasis on stochastic analysis, optimization, and/or functional analysis.

• Excellent graduatelevel understanding of probability theory, stochastic analysis, functional analysis and optimization, as evidenced for instance by a French DEA in maths, or the Cambridge Part III, prior to your PhD in Maths.
• Strong intuition to guide the design of reasonable conjectures from the geometry of the problem and background knowledge prior to attempting any proof.
• No finance or machine learning experience is required.