Research and deploy ultra-low-latency trading strategies by analyzing market data, developing exchange simulators and alpha signals, and measuring strategy performance and market competitiveness.
Applied Scientist
📜 Description
- Research how LLMs retrieve and reason over structured and geospatial data, including tool, API, text-to-query, and grounding approaches.
- Develop AI-ready representations of location data, such as geospatial embeddings, knowledge graphs, and structured context formats.
- Build benchmarks, evaluation datasets, and metrics for factuality and hallucinations in location-grounded systems.
- Design, train, and fine-tune machine learning models using large-scale multimodal data.
- Frame product opportunities as scientific problems with clear success metrics, then take solutions from prototype to production with engineering teams.
- Track advances in LLMs, retrieval, and agentic systems; communicate findings and share scientific knowledge.
🛠️ Requirements
- Bachelor’s, Master's or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Physics or a related quantitative field, or equivalent professional experience.
- Strong foundations in machine learning, deep learning, statistics and optimization.
- Hands-on experience with modern deep learning frameworks such as PyTorch or JAX, and with the Python scientific stack (NumPy, pandas, scikit-learn).
- Experience with one or more of: LLMs and generative AI, computer vision, time-series forecasting, graph neural networks, or reinforcement learning.
- Proven ability to design experiments, define meaningful metrics and draw sound conclusions from data.
- Experience working with large-scale datasets and distributed computing (e.g., Spark, Databricks, or cloud ML platforms on Azure, AWS or GCP).
- Ability to write clean, maintainable code and to work with engineers toward production deployment.
- Excellent communication skills, with the ability to explain complex technical ideas to diverse audiences.
- A track record of publications at top-tier venues (e.g., NeurIPS, ICML, CVPR, KDD) is a plus.
- Experience with geospatial, mapping, mobility or sensor data is a plus, but not required.
✨ Benefits
- A competitive compensation package, of course.
- Time to support life outside of work, with enhanced parental leave plus paid leave to care for loved ones and volunteer in local
- Improve your home office with a setup budget and get extra support with a monthly allowance.
- Enjoy options to work from your home country and abroad for a set number of days each year, to visit family and friends
- Take the holidays you want with a competitive holiday plan, plus an extra day off to celebrate your birthday.
- Join annual events like our Hackathon and DevDays to bring your ideas to life with talented teammates from around the world.
- Become a part of our inclusive global culture and have the chance to collaborate with a diverse community – we have over 80 nationalities
- Find out more about our global benefits and enjoy additional local benefits tailored to your location.
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