Marketing Science Senior Analyst - BI, Conversational Analytics & Data Engineering

Critical Mass•San Jose, CA

9d•Hybrid

About The Position

We are seeking a Marketing Science Senior Analyst to help design, build, and scale modern marketing analytics solutions that connect marketing investments to business outcomes. This role sits at the intersection of data engineering, analytics, measurement, and business intelligence, with a strong focus on developing robust data foundations, scalable reporting ecosystems, and AI-enabled analytics capabilities. You're equally comfortable building data pipelines, designing reporting frameworks, developing dashboards, and translating business questions into actionable insights. You will partner closely with Marketing Science, Media, Analytics, CRM, and Engineering teams to create scalable solutions that support enterprise B2B marketing measurement and decision-making.

Requirements

Bachelor's degree in Business Analytics, Computer Science, Engineering, Statistics, Mathematics, Economics, or a related quantitative field.
3-5 years of experience in Marketing Analytics, Business Intelligence, Data Analytics, Data Engineering, or Marketing Science.
Strong SQL skills and experience working with large and complex datasets.
Experience building and maintaining data pipelines, ETL/ELT processes, and data integration workflows.
Hands-on experience developing dashboards and business intelligence solutions.
Experience translating business needs into reporting requirements and analytical solutions.
Familiarity with cloud-based data platforms and modern data architectures.
Strong analytical, problem-solving, and stakeholder communication skills.

Responsibilities

Design, build, and maintain scalable data pipelines integrating marketing, CRM, web analytics, partner, and business outcome data.
Develop unified data models that support cross-channel measurement and reporting.
Establish data governance, documentation, taxonomy standards, and metadata management processes.
Implement data quality controls, automated validation checks, and anomaly detection mechanisms.
Support the development of scalable reporting datasets and semantic layers consumed by dashboarding and analytics tools.
Collaborate with technical teams to optimize data architecture, performance, and reliability.
Design and develop dashboards and reporting solutions for executive, operational, and campaign-level stakeholders.
Translate business objectives into KPIs, reporting frameworks, and measurement solutions.
Build scalable datasets, calculated metrics, and reusable reporting structures.
Support self-service analytics initiatives by creating intuitive reporting experiences.
Deliver regular performance reporting, campaign analysis, and insight generation.
Support Quarterly Business Reviews (QBRs), campaign recaps, and stakeholder presentations.
Develop and maintain measurement frameworks aligned to marketing and business objectives.
Define KPIs across demand creation, engagement, progression, conversion, and pipeline contribution.
Establish performance baselines and benchmarking methodologies.
Conduct analytical deep dives to identify opportunities for optimization and growth.
Support advanced analytics initiatives including attribution, forecasting, trend analysis, audience segmentation, and marketing effectiveness studies.
Partner with stakeholders to ensure measurement approaches evolve alongside business priorities.
Support the adoption of AI-enabled analytics and reporting capabilities.
Develop automated insight generation and performance monitoring processes.
Implement anomaly detection and alerting frameworks to proactively identify issues and opportunities.
Enable conversational analytics experiences that allow stakeholders to interact with data through natural language.
Evaluate emerging technologies that improve reporting efficiency and decision-making.
Partner with Marketing Science, Media, CRM, Analytics, and Engineering teams to align business requirements and technical solutions.
Present findings, insights, and recommendations to stakeholders in a clear and actionable manner.
Contribute to analytics best practices, governance standards, and documentation.