Job DescriptionWe're building the Data Science and ML capabilities that power an enterprise cybersecurity platform — analyzing billions of events, flows, logs, and identity signals to help customers detect risk before it becomes a breach. If you combine deep technical expertise with strong engineering leadership, this is your next big challenge.

NThis is a hands-on leadership role in a fast-moving startup environment, balancing technical depth, product thinking, execution, and team building.

NWhat You'll Own

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- Define and drive the technical vision, roadmap, and execution for Data Science, ML, AI, and advanced analytics capabilities
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- Build large-scale analytics solutions capable of processing billions of events, network flows, logs, identities, and security signals
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- Own Data Science/ML components end-to-end — from problem definition through production deployment, monitoring, and optimization
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- Apply supervised/unsupervised learning, anomaly detection, clustering, classification, and graph analytics to solve complex cybersecurity problems
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- Drive data preparation,feature engineering, model development, and experimentation across large, diverse security datasets
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- Build analytical and ML-based capabilities for threat detection, behavioral analysis, identity/access analytics, and security posture
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- Make key architectural and technical decisions, establishing engineering best practices for the function
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- Partner closely with Engineering, QA, UI, DevOps, IT/Ops, Product Management, and senior leadership to take solutions from concept to production
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- Build, mentor, and growa strong Data Science/ML team with a high technical bar
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- Evaluate and adopt advances in AI/ML, GenAI,



and graph analytics where they create real product value
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nWhat You Bring

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- 12+ years of hands-on experience in Data Science, ML, AI, Analytics, or a closely related field, with a robust record of building production-grade solutions
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- Strong hands-on expertise in ML/AI techniques, algorithms, and statistical methods
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- Deep understanding of supervised and unsupervised learning — classification, clustering, anomaly detection, dimensionality reduction
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- Strong programming experience in Python, with frameworks like NumPy, Pandas, Scikit-learn, NetworkX, and TensorFlow/Keras
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- Experience with large-scale datasets and distributed/cloud environments
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- Strong grasp of software engineering principles — architecture, scalability, reliability, performance, testing, CI/CD, production operations
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- Demonstrated ability totake ambiguous problems from definition to production solution
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- Bachelor's, Master's, or PhD in Computer Science, Data Science, Mathematics, Statistics, Engineering, or equivalent practical experience
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nGood to Have

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- Experience in cybersecurity, network security, identity security, or enterprise security analytics
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- Experience analyzing network traffic, flows, security events, audit logs, identity data, or telemetry
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- Event/log analytics platforms (ELK/OpenSearch or equivalent)
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- Graph analytics and graph-based ML (NetworkX or similar)
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- SQL, MongoDB, or equivalent
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- Distributed data processing (Spark or similar)
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- MLOps, model monitoring, and model lifecycle management
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- Experience applying LLMs/GenAI to cybersecurity or enterprise data analytics
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nYou see it a fit, then send your resume to [email protected] for more details.

📌 Head Of Data Science - Identity Security-Anomaly Detection Graph Analytics-Large-Scale Data Processi (India)
🏢 CareerXperts Consulting
📍 India