6 of 6 Remote/Hybrid XGBoost Jobs

Science, Mathematics, Statistics , or a related quantitative field. Scientific Python Ecosystem: Proficiency in Python for data science (pandas, numpy, scipy) and machine learning (sklearn, XGBoost, CatBoost, PyTorch). Data Engineering: Strong experience in SQL and data engineering principles (ETL/ELT), with the ability to handle large, complex datasets independently. ...

experience in ML/AI engineering or data science roles (senior level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record transitioning models from ...

/Azure acceptable) Experience with GenAI/LLMs (commercial or serious hands-on experimentation) Strong Python and modern ML tooling (e.g. scikit-learn, XGBoost, TensorFlow or PyTorch) Clear interest in crypto/blockchain (commercial experience a plus, curiosity required) Responsibilities Build, train, and improve ML models on large-scale blockchain ...

Mentor junior engineers and contribute to team best practices This role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live systems Experience with ...

colleagues and share learnings across the team. Requirements: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow. Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments. Strong experiment design skills: hypothesis formulation, A/B testing ...

modern AWS production environments. The Technical Reality: We operate a pragmatic stack where Linear Regression remains vital for stability and baseline performance, while XGBoost and LLMs are used as responsible additions. We are looking for someone who knows when to use a simple linear model and when to deploy … Responsibilities Predictive Modelling (Linear & Non-Linear): You will build and maintain foundational Linear Regression models for credit, affordability, and fraud scoring, while developing advanced XGBoost models for deeper risk insights. You will mine data to find behavioural signals—such as spending volatility or income stability—that predict affordability, repayment ...