Lead Software Engineer

Job Requirements

We are looking for a skilled Data Scientist – Anomaly Detection to develop, implement, and optimize machine learning and statistical models for identifying unusual patterns, abnormal behavior, and potential failures in complex datasets.

The candidate will work with historical and real-time data to detect anomalies, reduce false positives, identify emerging trends, and generate actionable insights. The role involves developing anomaly detection algorithms, performing exploratory data analysis, engineering relevant features, validating model performance, and deploying scalable detection solutions

Design, develop, and deploy anomaly detection models using statistical methods and machine learning algorithms.

Analyze large datasets to identify abnormal patterns, outliers, deviations, and unexpected behavior.

Perform exploratory data analysis (EDA), data profiling, and feature engineering to improve anomaly detection accuracy.

Develop detection approaches using statistical thresholds, clustering, isolation-based methods, and time-series models.

Build anomaly detection solutions for time-series data, operational KPIs, network performance metrics, and system events.

Develop models for detecting sudden spikes, drops, seasonal deviations, and gradual changes in performance

Build anomaly detection solutions for time-series data, operational KPIs, network performance metrics, and system events.

Develop models for detecting sudden spikes, drops, seasonal deviations, and gradual changes in performance

Work Experience

5-7Years