We'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 robust engineering leadership, this is your next big challenge.

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

What You'll Own

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



and graph analytics where they create real product value

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

Good to Have
- Experience in cybersecurity, network security, identity security, or enterprise security analytics
- Experience analyzing network traffic, flows, security events, audit logs, identity data, or telemetry
- Event/log analytics platforms (ELK/OpenSearch or equivalent)
- Graph analytics and graph-based ML (NetworkX or similar)
- SQL, MongoDB, or equivalent
- Distributed data processing (Spark or similar)
- MLOps, model monitoring, and model lifecycle management
- Experience applying LLMs/GenAI to cybersecurity or enterprise data analytics

You see it a fit, then send your resume to [email protected] for more details.

📌 Director Data ScienceB cybersecurity SaaS startup - Pune - CTC INR 100 L
🏢 CareerXperts Consulting
📍 Pune