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Senior Data Scientist Jobs

This list tracks 100K+ company job sources and updates hourly with senior data scientist roles across modeling, experimentation, forecasting, product analytics, decision science, and machine learning.

Openings range from senior and lead data scientists to principal data scientists, decision scientists, applied scientists, analytics directors, and data science managers. Work spans product measurement, pricing, risk, growth, operations, healthcare, finance, and other data-driven areas. The list helps separate experimentation and product-analytics positions from applied machine learning, forecasting, decision science, and data-science leadership. The clearest evidence of level usually appears in the responsibilities rather than the heading. Review the complexity of the work, autonomy, stakeholder seniority, team or program scale, and accountability for results. Then compare those expectations with the stated experience and credentials. This approach can reveal when a lead or principal opening remains hands-on, when a manager role carries substantial execution, and when a senior title implies broader organizational leadership. Use these distinctions to tailor your resume toward the leadership examples, domain decisions, and measurable outcomes most relevant to each opening.

Filter by company, location, industry, compensation, or sponsorship requirement. Review the original posting for required experience, degree expectations, technical tools, management responsibilities, and whether the role emphasizes statistical analysis, machine learning, or team leadership. Run a broad search once to learn the market's vocabulary, then refine it with the terms that recur in genuinely relevant postings. Use employer and location filters for practical constraints, and check compensation or sponsorship fields where available. Before applying, return to the source listing to confirm that availability and requirements have not changed and that the role still matches your intended work. A consistent comparison note for scope, requirements, workplace, timing, and next action makes repeated reviews faster and less subjective.

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7,532
roles in this list
3,150
added this week
Featuring roles at
Canva
Netflix
Notion
Visa
Capital One
& 100K+ more
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This list covers senior full-time roles in data science, applied machine learning, quantitative analysis, and clinical data science. Titles can include senior data scientist, principal data scientist, staff machine learning scientist, data science lead, and director of data science.

Data science roles often combine statistics, experimentation, analytics, modeling, and business interpretation. Machine learning roles usually emphasize model development, production systems, feature pipelines, evaluation, and applied AI delivery.

Highlight models, experiments, causal analysis, product or business decisions, measurable outcomes, data quality improvements, stakeholder influence, and examples where your analysis changed a roadmap, risk decision, forecast, or customer outcome.

Some roles prefer a master's or PhD, especially in research-heavy, machine learning, biostatistics, or quantitative domains. Many senior applied roles weigh industry impact, technical depth, communication, and product judgment heavily.

Expect statistics, experimentation, SQL or coding, modeling tradeoffs, product sense, metric design, stakeholder scenarios, and discussion of prior projects. ML-heavy roles may include system design, model evaluation, or deployment questions.

Compare data quality, decision authority, model ownership, engineering support, business impact, compensation, compute access, manager quality, and whether the team uses data science for real decisions or mainly reporting.

Senior data scientists usually own more ambiguous questions, statistical methods, modeling, experiments, and product or business decisions. Data analysts can be highly strategic too, but their work often centers more on reporting, dashboards, and descriptive analysis.