Applied machine learning and production systems define this Staff Data Scientist role at Jobber, where models serve product decisions in real time. Reporting to the Manager, Data Science, you will own automated decisioning models and systems. You will apply graph representation learning, transformers, ranking, and retrieval-augmented generation. The work spans training, evaluation, serving, monitoring, drift detection, and retraining. You will help make ML systems trusted, measurable, and reliable. Key Responsibilities:
Train and evaluate graph, transformer, ranking, and representation learning models Build RAG systems with reliable retrieval and context management Own production training, serving, monitoring, drift detection, and retraining Establish evaluation and regression testing for model quality Advance SignalGraph and its Neo4j and refresh pipelines Requirements:
End-to-end production ML experience serving real users Strong statistics foundation, including bias, variance, and loss functions Expert SQL and production-grade Python skills Hands-on deep learning, transformers, RNN, CNN, ranking, and LLMs Experience with large-scale data platforms and cloud infrastructure Bring production ML, statistical reasoning, and modern model expertise to Jobber’s applied machine learning systems.
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