Sr Search Analyst Consultant (Virtual)

About the Position

The Sr. Search Analyst / Consultant (SEM / SEO) analyzes large datasets to identify trends and opportunities, develop predictive models, and collaborates with our search team to improve campaign performance and profitability.

The individual identifies and scopes large, complex projects and breaks them down into manageable hypotheses and experiments to inform and develop analytical solutions, ultimately delivering business insights for planning and optimizing University of Phoenix marketing efforts.

The individual leads various work streams, which include other data and analytics professionals, in performing all aspects of data science, from data discovery, cleaning, model selection, and validation to deployment.

What You’ll Do :

1. Conduct ongoing analysis of SEM & SEO to identify areas for improvement and make data-driven recommendations to optimize campaigns from a variety of perspectives, such as conversion rates, keyword bids, impression shares, search queries, seasonal / geographical trends, keyword and ad copy research and development, landing pages, conversion funnel, quality score, and competition.

Track, report, and analyze the performance of our marketing activities and handle ad-hoc analytics requests.

2. Analyze large datasets to identify trends and opportunities for optimizing SEM & SEO using web analytics platforms such as Google Analytics, Bing Analytics, Google Search Console, Adobe Analytics, as well as utilizing database queries (SQL), AWS, Power BI / Excel, Python, and other software tools.

Collaborate with the search team to develop and implement data-driven strategies aimed at improving campaign performance.

3. Develop predictive models to forecast the performance of SEM & SEO and provide actionable recommendations to the search team, utilizing a deep understanding of bidding strategies and algorithms such as ROAS (Return on Ad Spend), CPC (Cost per Click), CPA (Cost per Acquisition), CPL (Cost per Lead), organic search KPIs, etc.

4. Develop and maintain dashboards and reports to effectively monitor and report on the performance of search channels to stakeholders.

Stay up-to-date with industry trends and advancements in search analytics to ensure our search strategies remain cutting-edge.

5. Leverage data science techniques and tools, statistical analysis, machine learning and predictive modeling to extract actionable insights from large datasets.

Develop models and algorithms to predict user behavior, optimize campaigns and improve conversions and revenue. Conduct exploratory data analysis and data mining, generate and test working hypotheses, analyze historical data and identify patterns.

6. Manage and execute large, complex projects, including data gathering and manipulation, synthesis and modeling, problem-solving, and communication of insights and recommendations.

Oversee the development and implementation of data integration and analytic strategies to support Marketing efforts.

7. Lead discussions with project stakeholders, senior Marketing leadership, and users to collaboratively define project scope and capabilities.

Identify and translate business requirements into artificial intelligence goals and modeling approaches. Rapidly iterate models and results to refine and validate approaches across different areas.

Translate advanced business analytics problems into technical approaches that yield actionable recommendations in marketing research.

8. Build ingestion processes to prepare, extract, and enrich a variety of structured and unstructured data sources, such as social media, news, internal / external documents, images, video, voice, emails, and operational data.

9. Propose and design compelling, meaningful, and effective data visualizations for reports, presentations, and analytical products to highlight key insights and relationships among features and research findings.

Ensure reports are created using credible qualitative and quantitative methodologies. Advise management and project stakeholders on appropriate / recommended courses of action based on final model output.

10. Perform other duties as assigned or apparent.

NOTE : The Primary Accountabilities above are intended to describe the general content and requirements of the position and are not intended to be an exhaustive statement of duties.

Incumbents may perform all or most of the Primary Accountabilities listed above. Specific goals or responsibilities will be documented in incumbents’ performance objectives as outlined by the incumbents’ immediate manager.

Supervisory Responsibilities

None

MINIMUM EDUCATION AND RELATED WORK EXPERIENCE :

• Bachelor's degree in Marketing, Business, Statistics, Data Science, or a related quantitative field. (e.g., Analytics, Operations Research, Computer Science, Applied Mathematics, Industrial Engineering)
• Three (3) years of experience in paid & organic search analytics with data science focus and a proven track record of developing and implementing successful search strategies for large campaigns

ADDITIONAL QUALIFICATIONS :

• Proficiency in using web analytics platforms such as SA360, Google Ads, Microsoft Ads and Smart bidding tactics and algorithms
• Having a deep understanding and hands-on experience in keyword research, bid management, and campaign optimization
• Knowledge of digital marketing concepts and best practices
• At least five (5) years of experience in paid and organic search analytics with data science focus, including management of large campaigns
• Master’s degree in Marketing, Business, Statistics, Data Science, or a related quantitative field. (e.g., Analytics, Operations Research, Computer Science, Applied Mathematics, Industrial Engineering) OR Ph.

D. in above fields and at least two (2) years of experience in search analytics

• Experience with machine learning, AI and predictive modeling techniques for search analysis and optimization (ML / AI models : regression, classification, clustering, dimensionality reduction methods, Markov Chain, Natural Language Processing (OCR, information extraction), Neural Networks / Deep learning, Generative AI, etc.)
• Knowledge of advanced analytics through data modeling, forecasting, simulation and data analytics taken from complex structured and unstructured high-dimensional datasets(Statistical analysis : time series analysis, media mix modeling, survival analysis, churn analysis, statistical inference, operations research, optimization and validation tools, etc.)
• Comfortable in cloud computing environments (Azure, AWS, GCP)
• Strong communication and presentation skills to effectively convey insights and recommendations to stakeholders
• Working knowledge of Adobe Analytics Suite
• Advanced skills in analyzing large datasets and extracting actionable insights
• Experience in deep learning frameworks and libraries (e.g., TensorFlow, Keras, PyTorch)
• Excellent critical thinking and logical reasoning skills, along with strong problem-solving skills, attention to detail, communication skills and time management ability
• Deep business understanding including potential impact of business decisions on various internal external stakeholders and systems
• Excellent verbal and written communication skills to effectively interact with internal and external customers and department staff
• Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
30+ days ago