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Established employer plus popular ML role, but NLP/transformer specialization reduces applicant density.
Specialized ML/NLP focus increases domain bias, yet skills are moderately transferable across industries.
Requires ML/NLP production experience and transformer expertise, but no explicit years, so medium strictness.
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Translate business goals into data science problem statements, success metrics, and experiment plans in collaboration with stakeholders.
Build, evaluate, and deploy machine learning and AI models using Python with focus on performance, robustness, and scalability.
Develop NLP solutions including text classification, entity extraction, topic modeling, semantic search, and summarization, managing full data science workflows end-to-end.
Strong proficiency in Python and machine learning techniques specifically applied to data science.
Experience with building and optimizing NLP systems using embeddings and transformer-based models.
Demonstrated experience designing experiments and running A/B tests to link model improvements to business outcomes.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in practical AI and modern ML/NLP techniques with a focus on explainability and measurable business impact.
Able to operate cross-functionally working closely with engineers, product, and business stakeholders.
Capable of managing end-to-end data science workflows and delivering reliable models in production environments.