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Capgemini
We are looking for an experienced Senior Data Analyst with a strong background in the Internet Service Provider (ISP) domain, specializing in the analysis of SD-WAN data and security device alerts. This role is central to leveraging AI and Machine Learning for anomaly detection, predictive analytics, and performance optimization across large-scale ISP networks.
You will play a critical role in transforming raw network and security data into actionable intelligence that improves uptime, customer experience, and security resilience.
Key Responsibilities:
Analyze high-volume data from SD-WAN components, routers, switches, and ISP-grade security appliances (e.g., firewalls, IDS/IPS, DDoS mitigation tools).
Correlate network performance issues and security alerts to uncover patterns, detect anomalies, and support incident prevention.
Design and implement AI/ML models for predictive maintenance, fault detection, traffic behavior analysis, and threat intelligence.
Conduct root cause analysis (RCA) for network outages, degradations, and security incidents affecting customer services.
Collaborate closely with NOC and SOC teams to deliver actionable insights for proactive monitoring and alerting.
Develop and maintain visualizations and dashboards (e.g., using Grafana, Power BI, Tableau) to report on key metrics and trends.
Ensure data quality, accuracy, and consistency across all network and security data sources.
Identify data-driven opportunities for improving network performance, security posture, and customer satisfaction.
Stay updated on industry best practices in AI/ML applications for ISP operations and cybersecurity.
Bachelor’s or Master’s degree in Data Science, Computer Science, Network Engineering, or a related field.
6+ years of experience in data analysis, with at least 3 years in the ISP or networking domain.
Strong knowledge of ISP network architecture, SD-WAN, BGP, DNS, DHCP, NAT, and other core protocols.
Hands-on experience with analyzing logs and alerts from security devices such as Fortinet, Cisco, Juniper, or Palo Alto.
Proficient in Python, SQL, and data analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
Practical experience with machine learning models for classification, clustering, anomaly detection, and time-series forecasting.
Experience working with SIEM tools and large-scale log data (e.g., ELK Stack, Splunk).
Strong problem-solving, critical thinking, and stakeholder communication skills.
Preferred Qualifications:
Background in large-scale ISP infrastructure monitoring and performance optimization.
Familiarity with ISP platforms and services (e.g., DNS, CDN, PPPoE, IP Management).
Experience with cloud networking tools (e.g., AWS/Azure network monitoring).
Relevant certifications (e.g., CCNP, CompTIA Security+, AWS Certified Data Analytics).
Exposure to big data tools (e.g., Spark, Hadoop) is a plus.
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