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Mid-level ML role, metro location, broad skillset and popular title drive high competition.
Core ML, Python, and cloud skills are broadly transferable across industries.
Explicit 3–6 years requirement plus mandatory ML frameworks, production deployment, and cloud skills increases strictness.
Analyze complex datasets to identify trends, opportunities, and insights for business impact.
Design, develop, validate, and deploy machine learning models including forecasting, classification, clustering, and anomaly detection.
Build data pipelines and collaborate with stakeholders and cross-functional teams to integrate and optimize data-driven solutions.
3-6 years of hands-on experience in Data Science or Machine Learning.
Proficiency in Python libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) and SQL for data manipulation.
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field.
Experience deploying machine learning models in production environments and familiarity with cloud platforms (Azure, AWS, GCP).
Experienced in building scalable machine learning models and managing end-to-end data science projects.
Skilled at translating business requirements into analytical solutions and effectively communicating insights via reports and dashboards.
Comfortable working with cross-functional teams including Data Engineers, BI Developers, and Product Owners to implement data-driven strategies.