Data Science Manager

Sentra is the global leader in cloud-native data security for the AI era. The company’s mission is to empower organizations to confidently scale their data operations across multi-cloud and on-premises environments while leveraging the power of AI without compromising security.

Sentra’s unique approach enables enterprises to autonomously scan their environments without the need for agents, ensuring that data remains securely within their cloud or on-premises infrastructure. This innovative methodology sets us apart in the industry, providing organizations with control and visibility over their sensitive data at all times. Our commitment to excellence in data security posture management and data detection and response makes Sentra a leader in the field.

We are seeking an experienced Data Science Team Lead to join us and play a key role in shaping the future of data security. As a Data Science Lead, you will be part of Sentra’s Classification team, which lies at the core of our mission - identifying sensitive data and helping customers detect the most critical risks in their cloud environments. Our multidisciplinary team of data scientists.

Responsibilities:

• Lead the end-to-end lifecycle (design, development, and deployment) of ML models (e.g., NER, LLMs) to advance our data classification and entity recognition capabilities.
• Partner with Product to align cutting-edge AI technologies with real-world customer needs and Sentra’s roadmap.
• Architect robust experimentation frameworks to accelerate model iteration, validation, and production deployment.
• Utilize extensive datasets to define quality benchmarks and drive continuous performance improvements.
• Champion innovation by identifying opportunities for automation and AI-driven features that maximize customer value.

Requirements:

• 7+ years of DS experience, with deep expertise in NLP and/or Generative AI.
• 3+ years leading DS teams (managing 3+ ICs), with a focus on team growth and mentorship.
• Proven track record of scaling ML models in production environments.
• Strong proficiency in Python, SQL, and modern ML frameworks.
• Hands-on experience with Big Data technologies, MLOps, and cloud-based AI infrastructure.
• Strategic mindset, with experience managing technical debt and defining long-term research roadmaps in Agile environments.
• Excellent communication skills, capable of translating complex technical insights for diverse stakeholders.

Nice to have:

• Prior experience in the data security or the compliance industry.
• Experience processing large amounts of data using Big Data tools like Spark.
• Experience using cloud based fine tuning frameworks.
• A Master’s or Ph.D. in a relevant field (e.g., Data Science, Computer Science, Statistics, Mathematics) is preferred.