Senior Data Scientist

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Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions.

The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate.

Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities.

Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Preferred Qualifications:

• Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications.
• Experience in Big Data preferably in the cybersecurity.
  Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc.
• Knowledge of anomaly detection, fraud detection, and other related areas.
• Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity

• Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions.
• Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response.
• Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment.
• Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks.
• Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models.
• Continuously monitor and improve the performance of ML systems to adapt to evolving threats.
• Lead the design and implementation of data-driven security solutions and tools.
• Mentor and guide junior data scientists in best practices and advanced techniques.
• Communicate findings and insights to stakeholders, including senior leadership and technical teams.