Expel Senior Data Scientist at Expel builds and ships machine learning and generative AI systems to detect threats and enhance analyst tools. The role involves collaborating across teams to deploy, monitor, and maintain AI and ML capabilities.
Responsibilities
Provide opportunities where your decisions have a direct impact on our company and our customers
Give you real, hard problems at the frontier of both GenAI and traditional ML in a security context
Empower you to scale yourself by teaching others what responsible, non-hyped AI looks like in practice
Challenge you to push the boundaries of our data science, security, and technology vision
Offer an entertaining, small, and highly transparent environment where your voice matters
Build and ship ML and GenAI systems — from anomaly detection models to LLM-powered analyst tools and agentic workflows — across the full lifecycle from research to production
Bring stakeholders along by clearly communicating the what, why, and how of your work, including successes and failures
Work across operations, engineering, and service delivery to ensure our AI and ML capabilities are easy to deploy, monitor, and maintain
Partner with subject matter experts to explore where prompt engineering, knowledge retrieval, and agentic AI can deliver real value alongside classical approaches
Foster an atmosphere of experimentation, continuous learning, and improvement
Stay current on emerging techniques, papers, and tools — and bring relevant ideas back to the team
Qualification
Solid grounding in traditional MLStrong Python and SQL skillsSolid statistical foundations
Required
Mentor and coach other data scientists and curious non-DS colleagues
4+ years of professional data science experience building and shipping models in production
Solid grounding in traditional ML: classification, regression, anomaly detection, clustering, time series — using frameworks like scikit-learn or statsmodels
Hands-on experience with large language models, prompt engineering, and LLM application architectures including knowledge retrieval and grounding (e.g., embeddings-based search, vector stores)
Experience building or contributing to LLM-powered agentic systems, including tool use and orchestration with frameworks like LangChain, LlamaIndex, or similar
Strong Python and SQL skills, utilizing core data libraries (pandas/numpy) and visual toolkits (plotly/seaborn/matplotlib) to transform complex analysis into clear, actionable insights for stakeholders and cross-functional peers
Solid statistical foundations: distributions, hypothesis testing, probability, and the wisdom to know when a simpler model is the right one
Exemplary collaboration skills that result in higher levels of team confidence and, morale, streamlining requirements gathering to drive superior output
Ability to communicate technical concepts clearly to non-technical audiences
Passion for finding order and meaning in large, chaotic data sets
Domain experience in cybersecurity (anomaly detection, threat hunting, risk scoring) is a strong plus
