● Develop and deploy AI models to enhance algorithmic trading strategies.
● Implement efficient data pipelines to collect, process, and analyze large-scale financial datasets.
● Design and optimize AI model training and inference pipelines for real-time and batch processing.
● Conduct research on quantitative trading techniques, deep learning, and NLP-based sentiment analysis.
● Collaborate with the trading and data engineering teams to refine models and improve performance.
● Optimize AI model deployment in on-premise infrastructure.
● Keep up to date with the latest advancements in AI, machine learning, and quantitative finance
Candidate requirements
● Strong knowledge of data structures and algorithms.
● Proficiency in Python and experience working with Linux-based environments.
● A solid mathematical mindset with knowledge in probability, statistics, and linear algebra.
● Familiarity with machine learning concepts and frameworks (eg, TensorFlow, PyTorch, Scikit-learn).
● Ability to read, analyze, and understand English technical papers and reports on AI and quantitative trading.
● At least 1 year of experience in:
■ Time-series modeling for financial data analysis.
■ Feature engineering to improve model accuracy.
● Experience in deploying models using Docker.■ Natural Language Processing (NLP), including sentiment analysis and entity extraction.
Preferred Skills (Nice to Have)
● Experience working with quantitative finance, trading algorithms.
● Understanding of backtesting frameworks for algorithmic trading.
● Familiarity with SQL and financial databases (eg, Bloomberg, Quandl, Alpha Vantage).
● Experience in deploying models using Docker.
● Mentorship from top AI and financial industry experts.
● Access to cutting-edge technology and resources for AI model training and deployment.
● State-of-the-art equipment provided for work.
● Team-building activities (monthly and quarterly) and an annual company summer trip.
● A professional, creative, and dynamic working environment.
● Flexible work schedule with a 5-day workweek (Monday – Friday).
● Competitive salary (to be discussed during the interview).
SUBMIT APPLICATION
● Timeline:
1. Round 1: CV Submissions (February 8, 2025 - February 14, 2025)
2. Round 2: Online Testing (February 14, 2025 - February 21, 2025)
3. Round 3: In-person Interviews (February 24, 2025 - February 28, 2025)