Business Intelligence Analyst - Marketing

NVIDIA•Santa Clara, CA

6d•$128,000 - $195,500

About The Position

NVIDIA’s Revenue Marketing Team is seeking a Business Intelligence Analyst to transform sophisticated marketing, sales, and developer data into actionable insights for the CMO and collaborators across Marketing, Sales, Developer, Finance, and Product. The role combines structured problem-solving with hands-on analytical expertise and an AI-native approach, using AI throughout the analytical process while developing reusable solutions and ensuring the accuracy and business impact of outcomes. The analyst will partner with senior leaders to frame business questions and guide initiatives from recommendations through adoption and measurement. They will synthesize analysis into executive briefs, presentations, and dashboards; present recommendations and advise on strategy, investment, and execution; and examine campaign performance, account journeys, funnel conversion, pipeline, and revenue attribution to identify growth opportunities. The role also applies statistical methods to evaluate hypotheses and develops AI-assisted and agentic workflows for analysis, anomaly detection, and reporting, validating results against source data and protecting critical information.

Requirements

At least 8 years of experience in management consulting at a strategy consulting firm or similar, synthesizing analysis and advising senior executives.
A degree or equivalent experience in Business, Economics, Analytics, Statistics, or a related field.
Proven ability to synthesize complex analysis into clear recommendations for senior executives.
Experience presenting and facilitating discussions in leadership meetings and influencing cross-functional decisions through adoption and measurable outcomes.
An AI-native working approach demonstrated through analytical workflows or tools built and used; ability to evaluate generated code and conclusions, identify errors, and apply human judgment.
Strong analytical judgment in statistical analysis, experimentation, attribution limitations, and distinguishing correlation from causation.
Ability to structure ambiguous questions and explain the implications and limitations of findings.
Experience building dashboards, data models, and visualizations in modern AI-first BI tools, emphasizing data storytelling, usability, and data quality.
Demonstrated ownership of analytical projects, strong documentation, and ability to influence cross-functional teams while delivering independently in a constantly evolving environment.

Nice To Haves

Track record of influencing senior executive decisions through presentations and business reviews, with recommendations adopted and measurable business outcomes.
SQL and practical Python familiarity, with hands-on experience exploring large datasets in a modern cloud analytics platform.
Familiarity with Salesforce, Marketo, Adobe Analytics, Tableau, or Amplitude.
Familiarity with account engagement, pipeline progression, lifecycle measurement, and proactive use of social listening data.
Examples of AI agents, analytical web apps, or automated intelligence briefs adopted by business users, with evidence of improved speed, accuracy, or decision making.
Experience with forecasting, marketing incrementality, or developer ecosystem analysis, including product usage and publicly available engagement data.

Responsibilities

Partner with senior leaders to frame business questions, challenge assumptions, and prioritize analysis based on business impact.
Translate leadership priorities into actionable plans and guide initiatives from recommendation through adoption and measurement.
Synthesize marketing, sales, and developer insights into concise executive briefs, presentations, and dashboards tailored to the audience.
Present recommendations to senior executives and lead discussions advising strategy, investment, and execution.
Explain analytical assumptions and tradeoffs, incorporate feedback, and build agreement on decisions and next steps.
Analyze campaign results, account journeys, funnel conversion, pipeline, and revenue attribution to identify growth opportunities and recommend resource priorities.
Apply statistical methods to test hypotheses, distinguish meaningful changes from noise, and assess the likely success of proposed actions.
Develop AI-assisted and agentic workflows to accelerate analysis, anomaly detection, and reporting.
Validate AI-generated outputs against source data, protect critical information, and evaluate whether insights positively guide decisions.
Own and document analytical projects, influence cross-functional teams, and deliver independently in an evolving environment.