13 of 13 Statsmodels Jobs

both statistically and commercially credible. Strong Python or R and SQL skills (joins, CTEs, window functions), with libraries such as pandas, NumPy, scikit-learn, statsmodels, or SciPy — and explainability tools like SHAP. Fluent in commercial concepts (ROI, ROAS, incremental revenue, margin, market share) and comfortable partnering directly with business-facing ...

software engineering fundamentals: version control, code review, automated testing, dependency and environment management. Machine learning across the standard toolkit (scikit learn, pandas, NumPy, statsmodels or equivalents), with sound judgement about model selection, validation and the limits of what the data supports. MLOps and CI/CD in practice, covering pipeline ...

translating technical methods to non-technical stakeholders Strong programming experience in Python and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain). R and C++ optional. Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis ...

computer vision, audio, graphs, time-series or tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying models using cloud platforms, particularly ...

interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with attention to cost ...

experience in translating technical methods to non-technical stakeholdersStrong programming experience in Python and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain). R and C++ optional.Experience with version control (GitHub)ML experience with causality, Bayesian statistics & optimization, survival analysis ...

computer vision, audio, graphs, time-series or tabular dataStrong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC)Understanding of software engineering and ML best practices, including version control, packaging and model deploymentExperience training and deploying models using cloud platforms, particularly AWSAbility ...

interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with attention to cost ...

testing the assumptions behind frequentist statsProficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)Well-versed in summarising, visualising and communicating findings in an accessible and compelling wayTrack record of influencing ...

proprietary research platform to support new exchanges, products and functionality.Python Developers Must Have:Expert in writing production level Python code including numpy, pandas, scipy, statsmodels etc (Python packages for numerical and statistical analysis)Able to take high level requirements and lead with constructing the engineering concept to underpin that projectExperienced ...

language each audience trusts. Essential Strong applied proficiency in Python and/or R, including modern data and ML libraries (e.g. pandas, scikit-learn, statsmodels or equivalents) and time-series/statistical forecasting methods. • A track record of owning an analytical product end to end – from data acquisition and modelling ...

research platform to support new exchanges, products and functionality. Python Developers Must Have: Expert in writing production level Python code including numpy, pandas, scipy, statsmodels etc (Python packages for numerical and statistical analysis)Able to take high level requirements and lead with constructing the engineering concept to underpin that projectExperienced ...

research platform to support new exchanges, products and functionality. Python Developers Must Have: Expert in writing production level Python code including numpy, pandas, scipy, statsmodels etc (Python packages for numerical and statistical analysis)Able to take high level requirements and lead with constructing the engineering concept to underpin that projectExperienced ...