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Remote posting, popular mid-level data scientist title, and 3–6 years experience increase applicant competition.
Core ML/AI skills are transferable across industries and no specialized finance domain expertise is mandated.
Explicit 5+ years, production ML and Generative AI requirements plus mandatory Python/R/SQL/cloud increase screening rigor.
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Design and implement advanced analytical and machine learning solutions for complex business problems, including end-to-end data pipelines and models.
Lead execution of complex data-driven projects from analysis through deployment with measurable business impact.
Provide technical guidance to data scientists and communicate complex insights and recommendations to senior stakeholders.
Bachelor’s degree in Computer Science, Statistics, Mathematics, or related field (or equivalent experience).
5+ years of professional experience applying data science, advanced analytics, and machine learning techniques.
Proficiency in Python, R, and SQL; experience with cloud-based data and analytics platforms.
Experience delivering AI/ML solutions in production and working knowledge of data visualization tools (QuickSight, Tableau, Power BI).
Experienced in designing data mining architectures and advanced analytical models for multi-domain business problems.
Skilled at integrating emerging AI/ML techniques including Generative AI into scalable solutions with measurable impact.
Capable of leading complex analytics projects and communicating technical insights effectively to senior business stakeholders.