Marketing Science, Senior Analyst

Critical Mass•San Jose, CA

22h•Hybrid

About The Position

As a Marketing Science, Senior Analyst, you'll be the data detective for an Automotive OEM brand, turning numbers into narratives and driving digital experiences to new heights. You bring three to five years of experience, leading marketing science deliverables across a broad range of initiatives and focusing on at least three of the following areas: tracking and measurement, implementation, reporting, data strategy, data engineering, data visualization, testing and evaluation, data integration, or statistical modeling. You have experience using data analytics to recommend solutions to improve digital marketing performance, enjoy collaborating with others, and are capable of directly communicating business insights to clients through logical, easy to understand stories. You will build deep knowledge of client business, make relevant recommendations, and identify actionable insights. Conduct in-depth analysis of complex site, app and media related data sets to uncover trends, patterns, and correlations. Develop and implement advanced statistical models and machine learning algorithms to solve business problems and optimize processes. Lead the ideation, development, and execution of measurement strategies and frameworks. Focus on developing expertise in measurement and strategy, involving the analysis of site related data to uncover insights, optimize performance, and drive strategic decisions. Additionally, you'll be responsible for devising strategies to enhance the user experience, improve app functionality, and analyze in-app survey results using NLP (natural language processing) and AI tools. Document data usage, gather requirements, and build/maintain dashboards to meet multiple teams’ needs. Support analytics tool implementation by defining, implementing, and validating tracking and data gathering strategies. Gather data through various third-party platforms. Implement data governance protocols to ensure the integrity, security, and privacy of app-related data, adhering to industry best practices and regulatory requirements. Create and maintain databases and data systems, ensuring completeness and accuracy of inputs and performing quality checks throughout. Challenge the status quo, looking for ways to continuously improve. Provide work direction to associate analysts and analysts. Participate in code reviews, coaching junior team members and improving data literacy within the organization. Occasionally contribute analytics content for pitch materials and RFPs (Requests for Proposal.) Opportunity to build and work on AI tools to impact business results.

Requirements

Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, or a related field.
Expertise in at least two of the following: data architecture (ETL/data integration), automated data ingestion + reporting, data science and statistical programming, testing and personalization, data visualization, analytics tool implementation.
Experience with Python, R, SQL, or other business-relevant statistical programming language.
Experience working within AWS infrastructure (Redshift, S3.) and Google Cloud Platform (GCP)
Experience with one or more visualization platforms (Tableau, Domo, Power BI, Datorama, etc.).
Experience with website measurement; either Google Analytics or Adobe Analytics, including tag management platforms (GTM, Adobe Launch, Tealium, etc.,) and one or more testing platforms (Optimizely, Adobe Target, etc.).
Strong verbal and written communication skills, attention to detail, and high standard of output.
Problem-solving skills: the ability to thrive in the face of ambiguity and move projects forward by actively removing barriers and defining next steps.
An understanding of the media landscape, ability to determine which channels are most appropriate based on business objectives, and experience using the data to make recommendations.
An understanding of how Search Engine Optimization (SEO) works alongside other channels, and experience analyzing it.
Three to five years of experience, leading marketing science deliverables across a broad range of initiatives and focusing on at least three of the following areas: tracking and measurement, implementation, reporting, data strategy, data engineering, data visualization, testing and evaluation, data integration, or statistical modeling.
Experience using data analytics to recommend solutions to improve digital marketing performance.
Capable of directly communicating business insights to clients through logical, easy to understand stories.

Nice To Haves

Tableau experience a plus.
Adobe analytics experience is a plus.

Responsibilities

Build deep knowledge of client business, make relevant recommendations, identify actionable insights.
Conduct in-depth analysis of complex site, app and media related data sets to uncover trends, patterns, and correlations.
Develop and implement advanced statistical models and machine learning algorithms to solve business problems and optimize processes.
Lead the ideation, development, and execution of measurement strategies and frameworks.
Focus on developing expertise in measurement and strategy, involving the analysis of site related data to uncover insights, optimize performance, and drive strategic decisions.
Devise strategies to enhance the user experience, improve app functionality, and analyze in-app survey results using NLP (natural language processing) and AI tools.
Document data usage, gather requirements, and build/maintain dashboards to meet multiple teams’ needs.
Support analytics tool implementation by defining, implementing, and validating tracking and data gathering strategies.
Gather data through various third-party platforms.
Implement data governance protocols to ensure the integrity, security, and privacy of app-related data, adhering to industry best practices and regulatory requirements.
Create and maintain databases and data systems, ensuring completeness and accuracy of inputs and performing quality checks throughout.
Challenge the status quo, looking for ways to continuously improve.
Provide work direction to associate analysts and analysts.
Participate in code reviews, coaching junior team members and improving data literacy within the organization.
Occasionally contribute analytics content for pitch materials and RFPs (Requests for Proposal.)
Build and work on AI tools to impact business results.