Researcher (data analysis)

19 hours ago

Karnataka, India AAA Global Full time

Bangalore, India Domain Focus: AI-Driven Algorithmic Trading, Deep Learning for Time Series Analysis Experience: 3+ years of experience in ML research for finance International Talent: Yes, international applicants are encouraged These roles are for technologists at heart, ML researchers eager to harness technology to transform traditional finance. We’re seeking professionals in Bangalore who can apply advanced techniques in AI, machine learning, and big data to develop next-generation trading strategies. The ideal candidates will have hands-on experience developing, implementing, and optimizing machine learning models that can process vast datasets and identify new sources of alpha. The roles we recruit for require individuals that thrive on building innovative, scalable systems from the ground up, pushing the boundaries of what is possible in quantitative finance. Career centred on applying machine learning research to practical, real-world challenges, ideally within finance. Background in technology-driven environments, with an emphasis on building robust, scalable systems. Proven record of driving projects that apply advanced ML techniques to novel data sources. Measurable contributions to trading team performance through new models or enhancements to existing ones. Projects And Performance: Successfully developed and deployed machine learning models that generated alpha or significantly improved trading strategy performance. Experience with the end-to-end ML lifecycle, from data sourcing and feature engineering to model deployment and monitoring. Ability to work in a collaborative environment, bridging the gap between theoretical research and practical, high-performance implementation. Experience in communicating complex technical concepts to a diverse team. Proficiency in Python and its data science ecosystem (e.g., Hands-on experience with deep learning frameworks (Tensor Flow, Py Torch) and big data technologies (e.g., Qualifications, Licenses And Academic Achievements: S. in a quantitative field is a significant advantage. Published research in machine learning, statistics, or a related field is highly regarded. #A collaborative researcher who can seamlessly integrate with a team of quants and developers. A mindset of continuous learning, a hunger to stay at the forefront of ML research, and an ability to adapt to new technologies.

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