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Niche AIOps specialization and seniority reduce pool, while moderate employer brand and metro hiring increase interest.
Deep IT-operations, telemetry, and ITSM domain expertise limits cross-industry transferability of candidates.
Explicit 15+ years overall, 8+ years data science, plus mandatory IT-ops/tool expertise create strict filters.
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Lead and manage end-to-end data science projects focusing on IT operations, ITSM platforms, and telemetry systems to drive operational efficiency and business value.
Develop predictive models and anomaly detection algorithms for incident forecasting, root cause analysis, and proactive remediation in IT environments.
Collaborate with IT architects, service owners, and automation teams to integrate AI-driven insights into operational workflows and create dashboards for technical and executive stakeholders.
15+ years overall IT & software experience with 8+ years in data science and at least 3 years specifically in IT operations or enterprise IT analytics.
Proficiency in Python, SQL, and data science libraries such as scikit-learn, pandas, TensorFlow.
Strong understanding of ITSM data structures, incident lifecycle, operational KPIs, plus experience with telemetry platforms like Nexthink, Intune, or similar.
Expertise in statistical modeling, machine learning (supervised, unsupervised), time-series analysis, and usage of AI/compute resources on MS Azure.
Experienced in handling complex IT operations data, telemetry, and cloud infrastructure metrics across platforms like Azure, AWS, or GCP.
Capable of independently managing multiple complex projects with strong cross-functional communication for executive reporting.
Familiarity or prior exposure to AIOps, DEX, EUC analytics domains, plus knowledge of ITSM tools like ServiceNow and MLOps frameworks is preferred.