Data Scientist – Ai & Cybersecurity

Siemens Healthineers; Karnataka; On-site; INR 3,000,000 - 4,500,000; Full time

Benefits offered by this job

Learning & development

Mentorship programs

Growth opportunities

Job summary

Siemens Healthineers seeks a senior Data Scientist to drive AI/ML solutions for enterprise security. You will define architecture, mentor teams, and partner with stakeholders to build scalable security analytics platforms.

Responsibilities include end-to-end DS lifecycle, threat detection models, and deployment in production environments. Strong Python, ML, and data engineering skills are essential for influencing product direction.

Qualifications

• Strong proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
• Deep expertise in supervised/unsupervised learning, deep learning, NLP/GenAI, and anomaly detection.
• Experience with large-scale security datasets (SIEM logs, network telemetry, cloud logs, EDR data).
• Hands-on experience deploying ML models in production (APIs, microservices, batch/stream pipelines).
• Knowledge of data architecture, feature stores, distributed computing, and data pipelines.
• Strong model evaluation, statistical methods, experiment design, and interpretability.
• Ability to translate ambiguous problems into structured analytical approaches.
• Excellent communication in cross-functional settings.

Responsibilities

• Lead end-to-end data science initiatives from problem definition to deployment.
• Architect and implement ML solutions for threat detection, anomaly detection, behavior analysis, fraud detection, malware classification, and predictive security analytics.
• Design scalable pipelines for large cybersecurity datasets (logs, telemetry, network, cloud signals).
• Drive research on GenAI, LLMs, graph models, and representation learning for security analytics.
• Collaborate with engineering, product, threat intel to operationalize models.
• Conduct model performance reviews, bias checks, and adversarial evaluations.
• Mentor AI/ML engineers and data analysts to foster innovation.
• Present findings and architectural recommendations to leadership.

Skills

Python

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

Supervised learning

Unsupervised learning

NLP/GenAI

Anomaly detection

Production ML pipelines

Model evaluation

Data architecture

Communication

Large-scale datasets

Education

Bachelor’s/Master’s/PhD in CS/DS/AI/ML/Statistics

Tools

MLflow

Kubeflow

Vertex AI

SageMaker

Job description

Role Overview

We are seeking an experienced Data Scientist to join our AI & Cybersecurity team and drive the design, development, and deployment of advanced analytical and machine learning solutions for enterprise security use cases. The ideal candidate should have strong expertise in data science, ML engineering, and applied research, with the ability to work across massive security datasets, uncover meaningful threat patterns, and influence product direction.

You will play a key role in defining architecture, guiding junior team members, and partnering with cross-functional stakeholders to build scalable, intelligence-driven security capabilities.

Key Responsibilities

• Lead the end-to-end lifecycle of data science initiatives—from problem definition, data exploration, feature engineering, model development, and evaluation to deployment.
• Architect and implement ML solutions for threat detection, anomaly detection, behavior analysis, fraud detection, malware classification, and predictive security analytics.
• Design scalable pipelines for ingesting and processing large volumes of cybersecurity data (logs, telemetry, network traffic, endpoint and cloud signals).
• Drive research on emerging AI techniques (GenAI, LLMs, graph models, representation learning) to strengthen security analytics.
• Collaborate closely with engineering, product, and threat intelligence teams to operationalize ML/AI models into production environments.
• Conduct model performance reviews, bias checks, adversarial evaluations, and continuous monitoring strategies.
• Mentor AI/ML engineers and data analysts, fostering a culture of innovation and technical excellence.
• Present findings, insights, and architectural recommendations to leadership and cross-functional stakeholders.
• Stay ahead on developments in AI/ML and cybersecurity and contribute to the long-term roadmap and strategy.

Must Have Skills

Experience: 8–12 years

Qualification: Bachelor’s/Master’s/PhD in Computer Science, Data Science, AI/ML, Statistics, or related discipline

• Strong proficiency in Python and ML/data science libraries (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
• Deep expertise in supervised/unsupervised learning, deep learning architectures, NLP/GenAI, and anomaly detection.
• Proven experience working with large-scale, high-dimensional security datasets (SIEM logs, network telemetry, cloud logs, EDR data).
• Hands-on experience with building and deploying ML models in production environments (APIs, microservices, batch/stream pipelines).
• Solid understanding of data architecture, feature stores, distributed computing, and data pipeline design.
• Strong grasp of ML evaluation, statistical methods, experiment design, and model interpretability.
• Ability to translate ambiguous problems into structured analytical approaches.
• Excellent communication skills with experience working in cross-functional settings.

Good to Have Skills

• Experience with MLOps platforms and tools (MLflow, Kubeflow, Vertex AI, SageMaker).
• Exposure to cybersecurity frameworks and concepts (MITRE ATT&CK, SOC operations, SIEM/SOAR tools).
• Experience with graph-based machine learning or network-level behavioral modeling.
• Knowledge of big data technologies (Spark, Kafka, Elasticsearch, Hadoop).
• Cloud experience (AWS, Azure, GCP) for ML workflow orchestration and scalable model deployments.
• Experience working with cybersecurity datasets (CICIDS, CTU-13, DARPA, malware datasets, DNS telemetry).
• Familiarity with LLM fine-tuning, vector databases, and embedding-based threat analysis.

What We Offer

• Opportunity to work at the intersection of AI, advanced analytics, and cybersecurity—shaping the next generation of intelligent security solutions.
• Ownership of high-impact initiatives involving large-scale enterprise datasets and cutting-edge AI techniques.
• Collaborative environment with strong support for experimentation, research, and innovation.
• Leadership visibility and growth opportunities into architecture, principal engineer, or data science strategy roles.
• Continuous learning culture supported by training, certifications, and mentorship programs.