At L2F - Learn to Forecast we conceive, develop and maintain highly sophisticated machine learning systems for large companies and public institutions.
We are one of the fastest growing start-ups in Switzerland and want to become #1 in the world at delivering solutions that address the most impactful data-driven challenges.
With an established research program in topological data analysis and already serving global players in IoT and manufacturing, Insurance, Telecommunications and other sectors, we are now entering the quantitative finance world.
As a Modeling Expert of our Investment Solutions department, you will be cracking complex challenges in various financial markets, developing and applying end-to-end data science techniques, from data processing to final model validation.
On a daily basis, you will:
What we look for
L2F people are self-motivated and resourceful individuals, eager to learn and leverage creativity, team and hard work to solve complex and fascinating challenges.
What we offer
Impact – You will work the pillar projects of the company and your contribution will directly affect our client’s growth and thus boost our own growth.
Environment – We are a young-spirited and cohesive team hungry for achievements. Our selective hiring process will allow you to work with extremely talented and passionate people.
Compensation – We offer a competitive salary, employee benefits package including health insurance and team activities and compensate the biggest efforts with L2F ownership.
Growth – You’ll be tested and challenged to go beyond your limits. If you put in the hard work and resolution it takes, we will provide you with the right tools (trainings, mentoring, increased exposition) to exponentially grow.
+41 78 940 2969
|Title||Modeling Expert – Investment Solutions|
|Employer||L2F - Learn to Forecast|
|Job location||EPFL Innovation Park, Building D, 1015 Lausanne|
|Published||October 29, 2018|
|Job types||Other  |
|Fields||Statistics,   Analysis,   Applied Mathematics,   Applied Physics,   Big Data,   Machine Learning  |