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Metro-based, mid-level data scientist role with production ML specialization yields moderate applicant competition.
Applied ML/MLOps skills transfer across industries, but domain-specific data and MDM knowledge increases sensitivity.
Requires PhD/Masters, 3+ years production ML, and specific tech skills, making filters strict.
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Design, implement, and deploy machine learning algorithms within a Python-based cloud architecture for production use.
Develop and release new data interaction capabilities using modern APIs and frameworks.
Deliver high-quality, automated, and maintainable code with potential involvement in CI/CD processes.
Master's or Ph.D. in quantitative/applied fields like Statistics, Computer Science, Engineering, etc.
Minimum 3 years of production-level machine learning development and deployment experience.
Proficiency in Python and SQL; knowledge of Spark, web services, and RESTful APIs.
Experience with cloud platforms (AWS, GCP, Snowflake) required; CI/CD familiarity preferred but not mandatory.
Experienced in building and deploying ML models in production environments with focus on data quality and accuracy.
Strong mathematical foundation in statistics, probability, ML theory, and related best practices including NLP, feature engineering, and A/B testing.
Comfortable working in agile teams and communicating effectively with remote stakeholders; demonstrates the ability to deliver solutions end-to-end.