We are looking for a Data Product Engineer who is experienced working within Azure cloud architecture using a variety of industry-standard tools (querying languages, reporting and data visualization) to achieve high-value insights for MTS clients. The Data Product Engineer will be challenged with analyzing a variety of data, both structured and unstructured, to support a variety of marketing initiatives, such as segmentation, campaign-planning inputs and performance analysis, KPI reporting and monitoring, and ways to drive more personalized one-to-one marketing efforts.
Additionally, the Data Product Engineer supports partner agencies analytics and reporting teams with expertise on integration of tools, data management and transformation needs, including ETL, within the MTS product ecosystem. The Data Product Engineer is fluent in each clients available data elements, performs data research & diagnosis, ensures satisfaction of data load and data transformation requirements, and supports partner agencies activating data virtualization capabilities, all in support of partner Agency Data Scientists fulfilling their analytic and reporting deliverables.
The role will revolve around the application of analytic techniques to drive and enhance the clients marketing performance across their multiple lead channels. To succeed in this role, the engineer is expected to demonstrate strategic thinking, logical reasoning, strong communication and presentation skills, outstanding analytic skills, and the ability to resolve complex issues.
Digital marketing, one of the fastest-growing businesses on the internet today, accounts for almost $70 billion of a $600 billion market.
MTS is innovating rapidly in the digital and computational marketing space to grow its share of this industry buy providing Omnicom agencies and its clients with a state-of-the-art marketing platform. MTS is at the core of this effort, responsible for research and development of all the product components in our marketing technology stack.
What Youll Do:
- Execute a wide variety of analytics projects including predictive modeling, individual profiling, campaign test design and analysis, dashboard reporting, demographic analysis, engagement recommendations, and individual segmentation.
- Extract and process large quantities of data from cloud data stores (Azure Blob, Azure SQL, Cosmos DB, etc.) in support of assignments.
- Support partner agency data scientists and analysts on the integration of third-party tools with the MTS product system
- Perform data research and diagnosis to ensure data load and transformation processes function as designed and meet partner agency requirements
- Design and implement ETL in support of accurate and efficient data ingestion and loading
- Analyze marketing metrics to identify cause-effect relationships between marketing levers and outcomes.
- Data mining and analysis, including the ability to independently QA database information, analytics outputs, drive platform enhancements via communication, and requirements documentation for technology teams.
- Build predictive models to drive customer acquisition and retention.
- Turn complex data into practical and actionable marketing insights.
- Develop test designs to support one-time and longitudinal test plans.
- Support development of efficient and accurate project management plans for project delivery.
What Youve Got:
Bachelors degree in computer science or equivalent in statistics, mathematics, economics or related scientific/quantitative field required. Advanced degree (M.A. or M.S.) preferred. Prefer 2-4 years of experience in the quantitative marketing arena, within a cloud environment and aligned with several of the bullets below.
- Proficiency with multiple analytics tools required (SQL, Python, Tableau, R, etc.).
- Experience creating and diagnosing statistical model performance and accuracy.
- Strong understanding of relational and NoSQL databases, Azure experience required.
- Hands-on, fluent experience with BI or digital analytics tools (Tableau, TIBCO Spotfire, Adobe Analytics, Adobe Audience Manager, Google Analytics, other DMP insight tools) preferred.
- Experience with statistical concepts and applying statistical techniques such as regression, ANOVA, cluster analysis, factor analysis, time series forecasting, machine learning, and experimental design.
- Ability to discover hidden insights or complex patterns through advanced multi-variate data mining techniques on unstructured business problems.
- Strong written, communication, and presentation skills.
- Previous experience delivering GDPR compliance approaches a plus.
- Experience with MS Office 365 (Word, Excel, PowerPoint, Outlook) required.
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