Senior Marketing Analyst – Audience Strategy & Insights-6376

Senior Marketing Analyst – Audience Strategy & Insights

itD is seeking a Senior Marketing Analyst to lead audience segmentation, audience strategy, and revenue opportunity sizing for the enterprise marketing team of a leading global technology organization. This role uses expert SQL and large, complex datasets to turn audience analysis into recommendations that shape business, product, and investment decisions. The ideal candidate will bring deep experience in marketing analytics, B2B audience and customer analysis, and data partnership with Data Scientists and Data Engineers, and a track record of delivering quantified audience strategies, segment libraries, and automated reporting that influence senior leadership.

Location: Hybrid – San Francisco, CA; New York, NY; or Menlo Park, CA (onsite presence required on a hybrid schedule).

Pay Rate: $50–$52 per hour, depending on experience.

Duration: 12 months, full-time (40 hours per week), with potential for extension.

We provide comprehensive medical benefits, a 401k plan, paid holidays, and more.

Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship.

 

Responsibilities

• Deliver deep audience analysis, including segmentation, lifecycle and funnel analysis, growth and churn signals, and revenue and adoption attribution.
• Size revenue opportunities and build the business case for which audiences to prioritize.
• Define how business questions should be answered, including what to measure, the methodology to use, and which assumptions apply.
• Pull, clean, and analyze large datasets (millions of records) using advanced SQL, reconciling data across sources and root-causing discrepancies before they reach reporting.
• Partner with Data Scientists and Data Engineers to define business logic, data models, and pipelines, and validate what is built.
• Build automated reporting and self-service dashboards that eliminate manual data pulls.
• Translate audience definitions into campaign-ready segments in a customer data platform, in partnership with campaign and lifecycle owners, and present findings and recommendations to senior leadership and cross-functional partners.

 

Internal Responsibilities

• Attend regular internal practice community meetings.
• Collaborate with your itD practice team on industry thought leadership.
• Complete client case studies and learning material (blogs, media material).
• Build out material to contribute to the Digital Transformation practice.
• Attend internal itD networking events (in person and virtual).
• Work with leadership on career fast-track opportunities.

 

Required Qualifications and Skills

• 8+ years of experience in marketing analytics, data science, data engineering, or business analytics.
• Expert-level SQL, including complex queries, CTEs, window functions, and query optimization across datasets of millions of records.
• Proven track record owning audience or customer analysis end to end: segmentation, lifecycle and funnel analysis, revenue opportunity sizing, and quantitative business cases with clearly stated assumptions and limitations.
• Hands-on experience with a customer data platform (preferably Salesforce Data Cloud) to build and activate segments.
• Demonstrated ability to partner with Data Scientists and Data Engineers on business logic and data pipelines, manage multi-source data across CRM, product, engagement, and third-party sources, and stand up automated reporting and dashboards (e.g., Tableau).
• Background in B2B marketing, sales, or customer analytics, with experience presenting to and influencing senior leadership and communicating with both technical and non-technical audiences.

 

Preferred Qualifications and Skills

• Hands-on pipeline building with dbt, Airflow, or equivalent orchestration tools.
• Experience with Hive and large-scale internal dashboarding environments, or comparable query and BI tools.
• Exposure to Salesforce Marketing Cloud and marketing automation workflows.
• Statistical modeling experience across propensity, LTV, attribution, forecasting, and experiment design.
• Fluency with CRM and account-level data models.
• Advanced Google Sheets/Excel, including pivot tables, lookups, and complex formulas.
• Basic Python for automation and API utilization.

 

Education

• Bachelor’s degree in a quantitative, technical, or business field, or equivalent practical experience, required.