as subject-matter expert for pricing models and valuation logic, supporting risk and trading teams globally. Skills and Experience Expert-level Python developer with strong experience in numerical computing (NumPy, SciPy, Pandas). Deep understanding of derivatives pricing theory, volatility modelling, and stochastic calculus. Experience with calibration, curve bootstrapping, and risk measures (Greeks, sensitivities, VaR). Background in pricing and More ❯
deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP/Azure, Docker, Kubernetes More ❯
concepts and assist the business with evaluations to measure success and estimate value proposition. Essential Criteria: * Extensive experience with Python and data science Python packages (e.g. scikit-learn, pandas, numpy, etc) * Understanding of data science concepts, AI/ML models, evaluation approaches, and data science applications to enhance business processes * Proven hands-on experience in Microsoft Azure ML Studio * Experience More ❯
as a Data Scientist , ideally in a government or large-scale enterprise environment. Strong Python programming skills, including experience with data science and AI/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services More ❯
as a Data Scientist , ideally in a government or large-scale enterprise environment. Strong Python programming skills, including experience with data science and AI/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services More ❯
for LLM fine-tuning, retrieval-augmented generation (RAG), and multi-agent AI workflows . Deliver production-grade Python code using advanced data science, ML, and analytics libraries (eg, Pandas, NumPy, Scikit-learn, PyTorch, Hugging Face Transformers, Pydantic ). Document and communicate AI designs, decisions, and experiment outcomes to both technical and non-technical stakeholders. Lead the design and deployment of More ❯
