Deep Learning Scientist - eFinancialCareers

Company Overview:

We are a distinguished firm known for our leading-edge research and development in the financial sector. With an emphasis on innovation and a collaborative culture, we strive to attract and nurture top-tier talent. Our workplace is crafted to encourage creativity and peak performance. At the heart of our operations is a commitment to a culture defined by collaboration, meritocracy, ambition, and determination—qualities that foster an ambitious and results-oriented atmosphere. Our investment strategies are systematic, supported by a robust research and development platform, with the goal of consistently delivering industry-leading returns.

Vision:

We value specialists who can immediately contribute and enhance our dynamic team with diverse skill sets and backgrounds. The computational models we are developing are becoming increasingly complex, and computational power is paramount.

The Opportunity:

1. Engage in an evolving environment that champions complexity and growth.
2. Work at the forefront of machine learning, recognizing and harnessing its transformative potential.
3. Thrive in a setting that combines the agility of a start-up with the stability of a well-funded entity—a perfect playground for innovation.
4. Experience mid to long-term growth opportunities, including leading teams and spearheading technology initiatives.

We Are Seeking:

Talented deep learning scientists who are eager to create and refine proprietary trading models and strategies. Our scientists collaborate closely with engineers, researchers, and senior leaders, with the scope to undertake independent research and develop new research themes over time.

Responsibilities Include:

1. Employing financial and other data sources to construct or enhance predictive models.
2. Utilizing state-of-the-art statistical and machine-learning models to bolster our R&D system.
3. Designing algorithms to capitalize on predictive signals.

Technical Qualifications:

1. Advanced degree (PhD or Postdoc) in finance, computer science, mathematics, statistics, machine learning, physics, or a related scientific discipline.
2. Strong mathematical, analytical, and problem-solving skills.
3. Experience conducting high-level statistical or applied mathematical research.
4. Prior quantitative trading environment experience is advantageous.
5. Proficiency in programming with C++, Java, or Python.