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Metro locations and popular ML title, moderate brand recognition, senior specialization.
Core ML skills transferable, but retail/supply-chain domain adds moderate domain sensitivity.
Extensive mandatory ML stack, deployment experience, and leadership expectations imply strict technical filters.
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Lead implementation and deployment of machine learning models, including data procurement, feature engineering, and model evaluation.
Ensure runtime deployment and monitoring of models for stability and performance.
Collaborate with product, sales, and engineering teams to develop retail AI solutions and support client engagements including sales material preparation and onsite meetings.
Bachelor’s Degree in Computer Science or related field; graduate degree preferred.
Proficient in Python programming with experience in data science libraries (Pandas, NumPy, TensorFlow, Keras).
Experience with SQL and familiarity with Big Data technologies such as Snowflake, Apache Beam/Spark, and Databricks.
Experience with cloud platforms preferably Google Cloud Platform (GCP) or Azure; work experience requirement: Not explicitly mentioned in the JD.
Experienced in deep learning, NLP, reinforcement learning, and combinatorial optimization techniques relevant to retail AI applications.
Proven ability to lead and mentor junior data scientists within official or unofficial settings.
Comfortable working in a cross-functional role involving data science, engineering, and sales to deploy machine learning solutions in a cloud-native, microservices environment.