Advanced Intraday Automation • Contact Center Automation • Real-Time Automation • Agent Development & Performance • WFM Automation
51 - 200
💰 $35M Debt Financing on 2021-11
Yesterday
Advanced Intraday Automation • Contact Center Automation • Real-Time Automation • Agent Development & Performance • WFM Automation
51 - 200
💰 $35M Debt Financing on 2021-11
• Develop mission critical mathematical models and algorithms as well as the supporting documents for the AI/ML initiative. • Read, discuss, and analyze: • Domain ontologies • Data models/schemas • Business problem statements • Technical documentations and definitions • Estimate, prioritize, and plan the activities associated with analysis and model creation. • Review algorithms for accuracy, performance, and appropriateness. • Be a subject matter expert on the tools and techniques used to develop and deliver quality AI algorithms. • Where necessary, troubleshoot and correct field issues in concert with other functional teams identifying root cause and corrective action. • Conduct all business in accordance with Intradiem’s development and security policies and procedures. • All other duties as assigned.
• Requires 5+ years of experience in AI/ML Solution Development as outlined above. • Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field with an emphasis on AI/ML methods or equivalent work experience. Master’s degree preferred. • Deep understanding of AI/ML technologies such as: • Genetic Algorithms • Quantitative Methods • Linear Programming • Non-Linear Programming • Time Series Decomposition/Analysis • Ontology Modeling • Graph Theory • Familiarity and/or interest in technologies used in realizing an AI/ML solution on a modern computing platform such as: • Programming languages (R, Python, etc.) • Data mining tools • Data presentation tools • Familiarity and/or interest in cloud related technologies such as: • Kubernetes • Docker • Ability/desire to research and understand the latest tools and technologies in the AI/ML space. • Experience with data pipelining, data platform, and data lake/warehouse technologies is desirable.
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