(Intern, Tokyo, On-Site, No-Visa-Provided) Research Scientist

We are hiring: Internship for Research Scientist — Reinforcement Learning / Bandit Algorithms for FX Trading (We do not like engineering trick, we do not like incremental work, we do not hire engineer. Instead, we want top-tier researcher with impactful research record in trading and AI) SAIL Lab Co., Ltd. is looking for a highly motivated Internship Research Scientist to join our team in Tokyo. Our core business is AI-driven FX trading. We are developing intelligent trading systems that combine reinforcement learning, bandit algorithms, statistical modeling, and market data analysis to optimize decision-making under uncertainty. Position: (Intern) Research Scientist Focus: RL / Bandit Algorithms / Quantitative Trading Location: Tokyo, Japan / Hybrid / Remote negotiable Annual compensation: up to JPY 15,000,000 We are especially interested in candidates with strong experience in one or more of the following areas: ・Reinforcement Learning ・Contextual Bandits / Multi-Armed Bandits ・Offline RL / Off-policy Evaluation ・Time-Series Forecasting ・Quantitative Finance ・Risk Modeling ・Backtesting and trading system development Required Qualifications * Ph.D. student or strong research experience in Computer Science, Machine Learning, Statistics, Financial Engineering, Operations Research, or a related field * Experience with FX, equities, commodities, futures, or other financial markets * Experience with backtesting, portfolio optimization, risk control, or trade execution * Experience with tick-level, intraday, or high-frequency financial data * Knowledge of market microstructure, transaction costs, slippage, and leverage management * Publications in top-tier venues such as ICML, NeurIPS, ICLR, KDD, WWW, AAAI, IJCAI, AISTATS, UAI, or related conferences * Japanese, Chinese communication ability is a plus but not required If you are passionate about applying cutting-edge machine learning research to real-world financial markets, we would love to hear from you. Please send your CV, publication list, GitHub profile, and a short statement of research interests to: [email protected]