Cohesity is looking for a Data Scientist to spearhead advanced
modeling, generative AI, and agentic workflows. This role combines deep
expertise in statistical and machine learning methodologies—ranging from
causal inference and time-series forecasting to reinforcement learning—with
hands-on development of transformer-based LLMs, semantic search, and
scalable AI system architectures. You’ll design production-ready features,
validate models through rigorous experimentation, and mentor a team to
execute Cohesity’s AI vision.

Data Scientist will contribute to Cohesity’s efforts in NLP, generative AI,
agentic development, and advanced data science modeling—driving design,
validation, and deployment of complex algorithms and scalable AI platforms.
You will translate business objectives into robust statistical and ML solutions,
overseeing end-to-end experimentation, model governance, and performance
optimization.

HOW YOU'LL SPEND YOUR TIME HERE:

• Lead development of predictive and prescriptive models—including deep learning, reinforcement learning, time-series forecasting, and causal inference pipelines—ensuring scientific rigor and production readiness.

• Design and execute statistical experiments and A/B tests, establishing robust validation frameworks and ensuring reproducibility.

• Design and implement robust experimentation frameworks—including A/B testing and causal inference methods—to evaluate AI-driven features and optimize product decisions.

• Oversee performance profiling, benchmarking, and resource-efficient deployment strategies to meet strict latency and cost targets.

• Develop and fine-tune transformer-based LLMs and orchestrate multi-agent workflows using frameworks like LangChain.

• Integrate retrieval-augmented generation and semantic search capabilities powered by vector databases (e.g., Pinecone, Milvus) into customer-facing solutions.

• Architect scalable, distributed AI platforms leveraging cloud/serverless technologies (AWS Lambda, Azure Functions) and GraphQL APIs for real-time inference.

• Drive performance profiling, benchmarking, and resource-efficient deployment strategies to meet strict latency and cost targets.

• Partner with Product, Marketing, Finance, and Engineering teams to build scalable data pipelines and real-time dashboards that deliver actionable insights.

• Translate complex modeling and AI concepts into clear narratives and presentations for stakeholders across the organization.
   

WE'D LOVE TO TALK TO YOU IF YOU HAVE MANY OF THE FOLLOWING:

• MS/BS in Computer Science/Computer Engineering or related field of study with 8-12 years of relevant experience.

• Expert proficiency in Python and software engineering best practices; Golang or Java experience is a plus.

• Hands-on with TensorFlow, PyTorch, and other deep learning frameworks; proven track record with transformer-based LLMs.

• Strong coding experience in Object Oriented Programming language.

• Deep expertise in statistical modeling, machine learning algorithms, and

• MLOps frameworks for model lifecycle management.

• Familiarity with AI ethics, governance, and data privacy framework (e.g., EU AI Act, IEEE Trustworthy AI)

• Experience scaling AI solutions in high-growth or startup environments under tight timelines.

• Demonstrated ability to leverage AI tools to enhance productivity streamline workflows, and support decision making.
  
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