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Mid-level ML role, metro location, generalist title and broad technical requirements increase candidate competition.
Core ML skills transferable across industries, but ELK and domain experience add moderate specificity.
Explicit 4+ years plus mandatory ELK, cloud, Linux, and cluster management increases technical filters.
Own end-to-end data science projects bridging business problems to data-driven solutions including data exploration, model creation, evaluation, and deployment as code.
Manage data processes and policies ensuring data security, privacy, accuracy, availability, and usability throughout the model lifecycle.
Diagnose and resolve complex production issues in distributed environments involving ELK Stack and cloud infrastructure tools.
Minimum 4+ years of relevant work experience.
Strong expertise in ELK Stack (Elasticsearch, Logstash, Kibana) for log management, monitoring, analytics, and distributed cluster management.
Experience working with Linux environments and cloud CLI tools (Azure CLI, AWS CLI, Kubernetes CLI).
Work Experience Required: Minimum 4+ years
Experienced in distributed environment troubleshooting and performance tuning with ELK Stack clusters.
Comfortable operating across business domains leveraging data science and engineering skills to solve complex operational problems.
Ability to communicate complex data insights and technical issues effectively to both technical and non-technical stakeholders.