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Senior Data Scientist

expel

Remote

Data

Posted 4 hours ago

Job Description

<p>You’re the kind of data scientist who gets equally energized by training a gradient boosted classifier and designing an LLM-powered agentic workflow. You understand that picking the right tool — whether that’s a decision tree, a language model, or a carefully chosen heuristic — matters more than chasing the latest trend. And you’re just as comfortable explaining your approach to a non-technical stakeholder as you are digging deep into a messy dataset.</p> <p>Does this sound like you? Great!</p> <p>We’re looking for a Senior Data Scientist to work across Expel, using both traditional machine learning and generative AI to solve meaningful problems. You’ll help teams develop the right metrics to measure what matters, build models that surface threats in our customers’ environments, and design AI-powered tools that make our analysts faster and smarter. Some of the most interesting work sits right at the intersection of GenAI and classical ML — and you’ll help us figure out where each approach wins.</p> <p>Our team values collaboration, curiosity, and a “how can I help?” attitude. If you care about making data science accessible to everyone — and find mentorship rewarding — let’s talk.</p> <hr> <h2><strong>What Expel Can Do For You</strong></h2> <ul> <li>Provide opportunities where your decisions have a direct impact on our company and our customers</li> <li>Give you real, hard problems at the frontier of both GenAI and traditional ML in a security context</li> <li>Empower you to scale yourself by teaching others what responsible, non-hyped AI looks like in practice</li> <li>Challenge you to push the boundaries of our data science, security, and technology vision</li> <li>Offer an entertaining, small, and highly transparent environment where your voice matters</li> </ul> <hr> <h2><strong>What You Can Do For Expel</strong></h2> <ul> <li>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</li> <li>Bring stakeholders along by clearly communicating the what, why, and how of your work, including successes and failures</li> <li>Work across operations, engineering, and service delivery to ensure our AI and ML capabilities are easy to deploy, monitor, and maintain</li> <li>Partner with subject matter experts to explore where prompt engineering, knowledge retrieval, and agentic AI can deliver real value alongside classical approaches</li> <li>Foster an atmosphere of experimentation, continuous learning, and improvement</li> <li>Stay current on emerging techniques, papers, and tools — and bring relevant ideas back to the team</li> <li>Mentor and coach other data scientists and curious non-DS colleagues</li> </ul> <hr> <h2><strong>What You Should Bring With You</strong></h2> <ul> <li>4+ years of professional data science experience building and shipping models in production</li> <li>Solid grounding in traditional ML: classification, regression, anomaly detection, clustering, time series — using frameworks like scikit-learn or statsmodels</li> <li>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)</li> <li>Experience building or contributing to LLM-powered agentic systems, including tool use and orchestration with frameworks like LangChain, LlamaIndex, or similar</li> <li>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</li> <li>Solid statistical foundations: distributions, hypothesis testing, probability, and the wisdom to know when a simpler model is the right one</li> <li>Exemplary collaboration skills that result in higher levels of team confidence and, morale, streamlining requirements gathering to drive superior output</li> <li>Ability to communicate technical concepts clearly to non-technical audiences</li> <li>Passion for finding order and meaning in large, chaotic data sets</li> <li>Domain experience in cybersecurity (anomaly detection, threat hunting, risk scoring) is a strong plus</li> </ul> <hr> <h2><strong>The Details</strong></h2> <p>The base salary range for this role is between $142,900 USD and $207,200 USD + bonus eligibility and equity.</p> <p>We believe in paying transparently and equitably. Your salary will ultimately be based on factors such as your experience, skills, team equity, and market data. You’ll also be eligible for unlimited PTO (which we model and encourage), work location flexibility, up to 24 weeks of parental leave, and really excellent health benefits.</p> <p><span style="font-weight: 400;">We're only hiring those authorized to work in the United States.</span></p> <p><span style="font-weight: 400;">We're an Equal Opportunity Employer: You will receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.</span></p> <p><span style="font-weight: 400;">We’ll ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please let us know if you need accommodation of any kind.</span></p> <p><span style="font-weight: 400;">#LI-Remote</span></p><div class="content-pay-transparency"><div class="pay-input"><div class="title">Salary Range</div><div class="pay-range"><span>$142,900</span><span class="divider">&mdash;</span><span>$207,200 USD</span></div></div></div>
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