Data Analyst
Experience 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.