Intradiem · 2 days ago

AI/ML Data Analyst

Remote, US

Full-time

Remote

Mid, Senior Level

5+ years exp

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Artificial Intelligence (AI)Machine Learning

Growth Opportunities

No H1B

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Responsibilities

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.

Qualification

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AI/ML Solution DevelopmentMathematical ModelsAlgorithmsGenetic AlgorithmsQuantitative MethodsLinear ProgrammingNon-Linear ProgrammingTime Series AnalysisOntology ModelingGraph TheoryRPythonData Mining ToolsData Presentation ToolsKubernetesDockerData PipeliningData PlatformData Lake/Warehouse

Required

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.

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.

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.