Data Scientist
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Overview:
The Internet Marketing Consultant or Data scientist is responsible for ensuring the execution of impactful Internet marketing reports and analysis that improve our client’s understanding of the performance of marketing efforts in order to help them make smarter marketing investments for our clients. The Internet Marketing Consultant is responsible for providing input into the strategic development of Rise’s client’s measurement framework and reporting. They will build reports, blend data from multiple sources, create predictive analyses, and help develop future predictive deliverables.
Responsibilities:
- Cross channel reporting including the compilation of performance data from platforms such as Google Analytics, Adobe Marketing Cloud, AdWords, Bing, DFA, et. al.
- Analyze data across platforms and generate into client facing deliverable (adheres to Rise best practices and standards for formatting, accuracy, and completeness)
- Assist Account Team in answering ad hoc web analytics questions in order to help explain changes in client performance.
- Develop predictive analytics deliverables, create strategy to accomplish predefined goals
- Drive predictive strategy and framework for clients
- Assist on other analytics projects including but not limited to conversion rate optimization, competitive intelligence, and predictive analytics.
Required Skills:
- Attention to detail – ability to craft client facing deliverables
- Ability to tell a story with data
- Functional knowledge of Excel – v lookups, pivot tables, exposure to VBA
- Ability to visualize data – experience with pivot charts, PowerPoint, other data visualization
- Ability to manage projects across multiple clients in varying industries
- Ability to manage competing tasks and priorities
- Familiarity working across multiple data sources and platforms
- Passion for innovation; willing to continuously evolve reporting, processes, and benchmarks for success
- Familiarity with advanced regression, clustering, CLV, RFM, product propensity, decision trees, and other related statistical analyses.
- Ability to understand client goals and conduct appropriate statistical analysis
- SQL and SAS experience and knowledge
- Ability to render statistical analysis in BI tools such as Domo, Tableau, or SAS Visual Analytics
- Coding expertise (ETL, Python, Java, .NET, Shell, R, or others)
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