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Popular mid-level Data Scientist role, metro location, broad ML skillset and known employer increase applicant competition.
Applied ML model development and deployment skills are broadly transferable across industries but require domain-specific tooling familiarity.
Extensive required ML skills and tooling imply moderate screening, but no explicit years reduces strictness.
Develop and implement machine learning models and algorithms to address business problems.
Collect, clean, and preprocess complex datasets for analysis to enable decision-making.
Collaborate with cross-functional teams to understand data needs and deliver AI-driven solutions.
Degree: Bachelor’s in Business Analytics, Computer Science, Statistics, or Master’s in Data Science.
Skills: Proficiency in AI, machine learning techniques, data preprocessing, and model validation; experience with tools like Amazon SageMaker and CI/CD pipelines.
Certifications: Preferred certifications include Deep Learning (Dimensionless Techademy) and Professional Machine Learning Engineer (InterPedia).
Work Experience Required: Not explicitly mentioned in the JD.
Experience thriving in fast-moving, innovation-driven environments focused on AI and advanced analytics.
Capable of synthesizing complex data and applying latest AI advancements to drive actionable business insights.
Comfortable working within hybrid work setup and collaborating across teams using agile and continuous integration methodologies.