We are seeking a highly motivated quantitative researcher to join our Investment Management & Research group, focussing on MENA Equities. You will play a key role in researching, developing and operating our equities strategies in the region, partnering with portfolio managers, researchers, and technology to build and optimise the full strategy lifecycle – from research and back testing to live trading and risk management.

You will spend an initial period of approximately 6 months working in our London office before relocating to our office in Abu Dhabi.

Your responsibilities will include:

• Conduct in-depth research to identify alpha-generating strategies in MENA equity markets
• Research and back test systematic trading signals
• Collaborate closely with portfolio managers, researchers and technologists to develop trading infrastructure and strategies
• Monitor, analyse and report on strategy performance

What we are looking for: 

• 3+ years of experience working in a systematic equity trading environment
• Proficiency in data analysis and programming, preferably using Python and key libraries such as Pandas and NumPy
• Exceptional understanding of signal research and portfolio construction
• Strong communication skills with the ability to work in a distributed and collaborative research environment.

Vatic Labs is a quantitative trading firm in New York and Abu Dhabi.  Our traders, AI researchers, and technologists collaborate to develop autonomous trading agents and cutting edge technology.  

As an AI Research Intern at Vatic Labs, you will contribute to the research and development of fully autonomous trading agents with some of the brightest researchers, traders, and technologists in the world. As a part of your internship at Vatic Labs, you will explore vast amounts of market data, research different AI approaches, apply cutting edge machine learning algorithms and statistical approaches to this data to discover and capitalize on trading opportunities.

We are seeking researchers who have demonstrated the ability to generate impactful research in their academic pursuits. We foster an open and academic environment, where collaboration is the key to our success. Drawing from our collective backgrounds in Computer Science, Mathematics, Statistics, and Physics, we apply rigorous analytics to test hypotheses derived from years of successful quantitative trading. We are passionate about hiring the best and the brightest, empowering them with the tools and mentorship needed to be successful.

If you possess the following, we would love to explore what is available for you with our team:

• Earned or will earn a PhD or Master's Degree in Computer Science, Statistics, Mathematics, Electrical Engineering, Physics, or related fields
• Demonstrable experience coding in C++ or Python in a Linux environment
• Have experience analyzing large datasets with rigorous statistical and machine learning approaches, including classification, clustering, and regression.
• In depth technical knowledge of AI, deep learning, and machine learning algorithms including strong knowledge of the mathematical underpinnings behind these various methods
• Have innate curiosity for understanding why and how certain techniques work
• Have deep knowledge of time-series analysis
• Advanced knowledge of a high-level language for numerical analysis, Python (numpy/scipy stack) preferred
• Contribution to AI and ML research communities, top tiered peer reviewed publications, publishing/presenting papers at conferences such as NIPS, ICML,  etc.
• Have an interest and enthusiasm for learning about financial markets (previous experience not required)

As a Quantitative Researcher at Vatic, you will research and develop innovative quantitative strategies. You’ll explore large-scale market data, applying novel machine learning and artificial intelligence methods to discover and capitalize on trading opportunities. The problems are challenging; we hire top talent, empower them with tools and mentorship, and foster a highly collaborative, open environment. Our researchers are recognized leaders whose work is widely cited in top-tier, peer-reviewed journals.

What You’ll Do

·      Formulate and test hypotheses on vast, multi-modal market datasets.
·      Build and evaluate ML/AI models (e.g., classification, clustering, regression) to identify alpha.
·      Design robust research pipelines and backtests; iterate from idea → signal → portfolio contribution.
·      Collaborate with engineers to productionize strategies and improve research tooling.Required Qualifications
·      PhD or Master’s (earned or in progress) in Computer Science, Statistics, Mathematics, Electrical Engineering, Physics, or related fields.
·      Relevant industry experience, or experience as a Postdoc/Faculty in a scientific lab.
·      Proven ability to analyze large datasets with rigorous ML/AI approaches.
·      Demonstrated ability to generate impactful research (academic or professional).
·      Deep knowledge of time-series analysis.
·      Advanced proficiency in a numerical language; Python (NumPy/SciPy stack) preferred.
·      Exposure to C++ or a related compiled language.
·      Interest in financial markets.Nice to Have
·      Experience with portfolio construction, risk modeling, and transaction cost analysis.
·      Familiarity with distributed computing frameworks and research workflow tooling.
·      Publications or open-source contributions in ML/stats or related areas.What We Value
·      First-principles thinking, high ownership, and a bias for rigorous experimentation.
·      Clear communication and collaboration across research and engineering.
·      Curiosity, humility, and continuous learning.

At Vatic, we’re serious about our work—but we also believe in balance, growth, and having fun along the way. Here’s what you can expect:

• Flat structure with direct executive exposure – Work closely with leadership and make an impact from day one.
• Comprehensive health benefits – Full health insurance coverage for employees and dependents.
• Daily meals provided – Enjoy free lunch at the office.