Senior Data Scientist IT Operations & Analytics

• Lead end-to-end data science projects focused on IT operations, incident management, and experience optimization.
• Analyze structured and unstructured data from ITSM systems, endpoint telemetry platforms, and infrastructure monitoring tools.
• Develop predictive models for incident forecasting, root cause analysis, and proactive remediation.
• Design anomaly detection algorithms to identify performance degradation, user friction, or compliance risks.
• Build dashboards and visualizations to communicate insights to technical and executive stakeholders.
• Collaborate with IT architects, service owners, and automation teams to embed intelligence into operational workflows.
• Evaluate data quality, lineage, and governance across diverse IT data sources.
• Stay current with emerging trends in AIOps, DEX, and IT analytics.

Job Requirements

• Overall 15+ years of experience in IT & Software, with at least 8+ years in data science and 3+ years focused on IT operations or enterprise IT analytics.
• Proficiency in Python, SQL, and data science libraries such as scikit-learn, pandas, and TensorFlow.
• Strong understanding of ITSM data structures, incident lifecycle, and operational KPIs.
• Experience with telemetry platforms like Nexthink, SysTrack, Intune, and SCCM, along with endpoint data.
• Familiarity with cloud infrastructure metrics (Azure, AWS, GCP) and log analytics.
• Expertise in statistical modeling, machine learning, and time-series analysis.
• Ability to work independently and manage multiple complex projects simultaneously.
• Expertise in using compute and AI resources on MS Azure.
• Expertise in using statistical unsupervised models, supervised models, LLMs, and SLMs.
• Excellent communication skills for cross-functional collaboration and executive reporting.
• Preferred Qualifications: Experience in AIOps, DEX, or EUC analytics domains.
• Knowledge of ServiceNow, performance analytics, and integration workflows.
• Exposure to MLOps frameworks and model deployment in enterprise environments.
• Advanced degree in Computer Science, Statistics, or a related field.

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