Quantitative Finance Researcher

Role We are looking for an experienced Macro Quant Researcher to join our team in Taipei. Responsibilities Develop macro-focused systematic trading strategies in liquid secondary markets. Conduct research to identify data-driven signals and market inefficiencies. Collaborate with team members on research and development initiatives. Requirements B.S., M.S., or Ph.D. degree in economics, finance, computer science, physics, or other quantitative discipline. 2+ years of experience in quantitative research or systematic trading at a bank, hedge fund, or asset manager. Experience with systematic trading strategies for any secondary market product (e.g., Taiwan index futures, BTC, etc.) using tools beyond Excel or MultiCharts. Proficiency in Python or C++ and familiarity with database query languages (SQL or NoSQL). Demonstrable ability to conduct independent research utilizing large datasets. Detail-oriented, willingness to take ownership of his/her work, and ability to work both independently and within a small team. Commitment to the highest ethical standards.

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. WHAT YOU'LL DO The Quant Developer will be responsible for building and maintaining the research infrastructure and backtesting frameworks that support quantitative research, working closely with researchers to translate research ideas into robust, scalable, and maintainable research systems. The role spans multiple areas, including system design, data pipeline development, and the development of research and backtesting frameworks. WHAT'S REQUIRED Background in Electrical Engineering, Computer Science, or a related field, with 3+ years of software development experience as a software engineer. Strong programming ability in C++ and Python. Solid command of CI/CD practices and tooling, with the ability to design and maintain automated testing and build pipelines for research and backtesting environments. Practical knowledge and hands-on experience with distributed computing and distributed job scheduling / task assignment. Excellent analytical and engineering problem-solving skills. Demonstrated ability to work independently on large datasets and large codebases. A strong team player who works closely with researchers to translate research ideas into stable, maintainable research systems. Willingness to take ownership of your work, able to operate both independently and within a small team, while remaining careful, detail-oriented, and capable of performing well under pressure. Strong English communication skills. Commitment to the highest ethical standards. We take care of our people We invest in our people, their careers, their health, and their well-being. When you work here, we provid

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. We are seeking an experienced Data Science Manager to lead a team of data scientists and analysts focused on developing data-driven solutions that optimize cost, drive efficiency, and unlock value across procurement and manufacturing value engineering. In this role, you will own the delivery, and people leadership for a portfolio of cost-related analytics and AI initiatives, translating complex business challenges into measurable cost impact. You will also champion the adoption of cutting-edge AI, including Generative AI and agentic systems to accelerate how the team delivers cost solutions. Key Responsibilities Team Leadership & People Management Lead, mentor, and grow a team of data scientists. Set clear goals, conduct performance reviews, and support career development. Foster a collaborative, high-accountability culture of experimentation and continuous learning. Manage hiring, onboarding, and resource allocation across projects. Solution Development & Delivery Oversee end-to-end development of models and tools for cost forecasting, cost-leakage/anomaly detection, and scenario/what-if analysis. Drive analytics for manufacturing value engineering—identifying cost-down opportunities across design, materials, processes, and supplier options. Ensure solutions are production-ready, scalable, and integrated into business workflows and decision-making. Establish best practices for model development, va