Senior Data Scientist

Bitsight is a cyber risk management leader transforming how companies manage exposure, performance, and risk for themselves and their third parties. Companies rely on Bitsight to prioritize their cybersecurity investments, build greater trust within their ecosystem, and reduce their chances of financial loss.

Built on over a decade of technological innovation, its integrated solutions deliver value across enterprise security performance, digital supply chains, cyber insurance, and data analysis.

• We invented the cyber ratings industry in 2011
• Over 3000 customers trust Bitsight
• Over 750 teammates are dispersed throughout Boston, Raleigh, New York, Lisbon, Singapore, and remote

Cybersixgill a Bitsight company, is looking for a talented Customer Success Manager (CSM) to join our team. A successful candidate will be comfortable working in a team as well as independently, with high motivation to solve unique problems.

In this role, the CSM will be responsible for onboarding new customers, guiding them through the adoption of our products and services, ensuring satisfaction, guaranteeing retention, and facilitating expansion. A successful CSM will build strong relationships with the customers and communicate customer needs and expectations to other departments within the company.

Job Description

We’re looking for a Senior Data Scientist who can take ideas from exploration to production. You’ll own projects end-to-end, from identifying opportunities in massive, complex datasets to working hand-in-hand with engineering to ship reliable, scalable systems.

Our data spans millions of signals collected from across the deep and dark web, offering a unique opportunity to build intelligence from highly unstructured, dynamic information. You’ll use this data to design and deploy retrieval-augmented generation (RAG) systems that efficiently search, organize, and contextualize information and then extend these capabilities using large language models (LLMs) for reasoning, summarization, and automation at scale. The role blends research, experimentation, and hands-on implementation, with a clear path to production impact.

Responsibilities

• Research, design, and implement LLM end-to-end pipelines using RAG, agentic solutions and MCP servers.
• Collaborate closely with the engineering team to move prototypes into production, ensuring scalability, reliability, and maintainability.
• Develop and maintain classic ML solutions, with a broad understanding of traditional data science workflows.
• Build evaluation frameworks to measure model accuracy, performance, and robustness in real-world settings.
• Partner with cross-functional teams to define data needs, success criteria, and system integration points.

Requirements

• 4+ years of industry experience in data science or applied machine learning, with a record of shipping models to production.
• Bachelor’s degree in Data Science, Computer Science, Computer Engineering, or related field.
• Strong programming skills in python.
• Deep understanding of prompt engineering and evaluation techniques, including few-shot design, RAG grounding, and hallucination mitigation.
• Hands-on experience with LLM orchestration frameworks such as LangChain for building agent-based systems.
• Familiarity with software development best practices, including version control (Git), Docker, and experience with data systems such as MongoDB and Elasticsearch.
• Strong communication skills and the ability to collaborate closely with engineering.
• A practical mindset — able to turn complex ideas into working, impactful systems.

Preferred qualifications

• Master's or Ph.D. Degree in a quantitative field.
• Experience fine-tuning and deploying large language models using frameworks such as Hugging Face Transformers, vLLM, or SageMaker.
• Interest in cybersecurity and applying ML/AI to real-world risk and security problems.
• Skilled at sharing knowledge through presentations, internal training, or public talks.