Data Science Manager

Company Description

Quick Heal Technologies Limited is a leading provider of IT Security and Data Protection Solutions with a strong presence in India and a growing global footprint. Founded in 1995, we cater to B2B, B2G, and B2C segments, offering solutions across endpoints, network, data, and mobility. Our state-of-the-art R&D center and deep threat intelligence enable us to deliver top-tier protection against advanced cyber threats. Known for our renowned brands 'Quick Heal' and 'Seqrite', we are committed to our employees' development, and societal progress through cybersecurity education and awareness initiatives. Quick Heal is the only IT Security product company listed on both BSE and NSE.

Role Description

We are seeking a Data Science Manager to lead a high-performing team of data scientists and ML engineers focused on building scalable, intelligent cybersecurity products. You will work at the intersection of data science, threat detection, and real-time analytics to identify cyber threats, automate detection, and enhance risk modelling.

Responsibilities

• Lead and mentor a team of data scientists, analysts, and machine learning engineers.
• Define and execute data science strategies aligned with cybersecurity use cases (e.g., anomaly detection, threat classification, behavioral analytics).
• Collaborate with product, threat research, and engineering teams to build end-to-end ML pipelines.
• Oversee development of models for intrusion detection, malware classification, phishing detection, and insider threat analysis.
• Manage project roadmaps, deliverables, and performance metrics (precision, recall, F1 score, etc.).
• Establish MLOps best practices and ensure robust model deployment, versioning, and monitoring.
• Drive exploratory data analysis on large-scale security datasets (e.g., endpoint logs, network flows, SIEM events).
• Stay current on adversarial ML, model robustness, and explainable AI in security contexts.

Required Qualifications

• Bachelor's or Master’s degree in Computer Science, Data Science, Statistics, or a related field. Ph.D. is a plus.
• 7+ years of experience in data science or ML roles, with at least 2+ years in a leadership role.
• Strong hands-on experience with Python, SQL, and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience working with security datasets: EDR logs, threat intel feeds, SIEM events, etc.
• Familiarity with cybersecurity frameworks (MITRE ATT&CK, NIST, etc.).
• Deep understanding of statistical modelling, classification, clustering, and time-series forecasting.
• Proven experience managing cross-functional data projects from conception to production.

• Preferred Skills

• Experience with anomaly detection, graph-based modelling, or NLP applied to security logs.
• Understanding of data privacy, encryption, and secure data handling.
• Exposure to cloud security (AWS, Azure, GCP) and tools like Splunk, Elastic, etc.
• Experience with MLOps tools like MLflow, Kubeflow, or SageMaker.