Data Analyst

Brief DescriptionData AnalystExperience Level: 3 - 5 years About the Role We are looking for a Data Analyst with strong analytical skills and a keen interest in web infrastructure and behavioural analytics to support the development of an ML-based anomaly detection system for NGINX server logs. You will play a critical role in extracting domain knowledge from raw logs, identifying behaviour patterns, anomalies, and translating these into insightful features that inform our ML engineers and are used for real-time dashboards. This is not just a reporting role — you will work alongside AI engineers and data engineers to shape how raw data is interpreted and transformed for machine learning and operational use. Key Responsibilities Domain Behaviour Analysis:

Analyse large volumes of log data to identify user behaviour patterns, anomalies, and security events. Interpret fields such as IP addresses, geolocation data, user agents, request paths, status codes, and request times to derive meaningful insights.

Feature Engineering Support:

Collaborate with AI engineers to propose relevant features based on log behaviour and traffic patterns (e.g., burst patterns, unusual request headers, request frequency shifts). Validate engineered features against behavioural patterns and business context. Conduct exploratory data analysis (EDA) to evaluate feature quality and distribution.

Data Visualization & Dashboards:

Develop data visualizations to represent time-series trends, geo-distributions, traffic behaviour, etc... Collaborate with the frontend/dashboard team to define and test visual requirements and anomaly indicators. Help surface visual insights on anomalies and their severity for analyst consumption.

Data Quality & Validation:

Identify and address gaps, inconsistencies, and errors in raw logs. Ensure feature logic aligns with real-world HTTP behaviour and use cases.Documentation & Knowledge Sharing: Create documentation that explains observed behavioural patterns, feature assumptions, and traffic insights for use by the wider ML and security team.

Minimum Qualifications

Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Cybersecurity, or a related field. Min 3 years of experience in data analysis or analytics roles. Proficiency in: SQL, Elasticsearch queries (DSL or Kibana), Python for data analysis (pandas, matplotlib, seaborn, plotly) Experience working with web server logs (NGINX, Apache) or structured event data. Strong analytical thinking — ability to break down complex log behaviour into patterns and outliers.

Nice to Have

Familiarity with web security concepts (DDoS, bot detection, HTTP protocol). Experience with log analytics platforms (Kibana, Grafana, ELK Stack). Understanding of feature engineering concepts in ML pipelines. Experience working on or with anomaly detection or security analytics systems. Preferred SkillsSQLPythonNGINXApacheElasticsearch queries