Director, Cross-Channel Attribution Modeling (REMOTE)
Merkle is a leading data-driven, technology-enabled, global performance marketing agency that specializes in the delivery of unique, personalized customer experiences across platforms and devices. For more than 30 years, Fortune 1000 companies and leading nonprofit organizations have partnered with Merkle to maximize the value of their customer portfolios. The agency’s heritage in data, technology, and analytics forms the foundation for its unmatched skills in understanding consumer insights that drive people-based marketing strategies. Its combined strengths in performance media, customer experience, customer relationship management, loyalty, and enterprise marketing technology drive improved marketing results and competitive advantage. With 9,600+ employees, Merkle is headquartered in Columbia, Maryland, with 50+ additional offices throughout the US, EMEA, and APAC. In 2016, the agency joined the Dentsu Aegis Network. For more information, contact Merkle at 1-877-9-Merkle or visit www.merkleinc.com.
The Director will be an integral part of our US-based modeling capabilities, conducting advanced analytical analyses of marketing activities and estimating their impact on sales. These projects will include, but are not limited to, Media Mix Optimization, Analysis of Covariance (test & control), Cluster Analysis and Attribution Modeling of disaggregate event-stream data. This person will be a “player coach”; in somce cases, the Director coordinate with some of our most important clients on data acquisition, deconflicting and presentation of results, as well as collaboration with multiple levels of the Merkle organization on high-visibility projects. In other cases the Director will be hands-on keyboard helping to revise code, drive innovation and manage our cloud-based environment. This role has direct and indirect leadership responsibilities (management of shared overseas modeling resources)
· Coordinate and manage data collection with clients
· Develop reports and processes to manage data quality control
· Supervise and, as needed, conduct modeling of client data, often in compressed timelines
· Interpret and visualize model estimates and diagnostics
· Support client teams to deliver insights on model results
· Drive process innovation and continuous improvement
Key Skills and Experience
- Minimum of 8 years as an Analtyics Sr Manager or equivalent experience
· Advanced degree in at least one of these fields: statistics, applied mathematics, optimization, computer science, physics
· Deep knowledge of statistics / data science, including regression, especially hierarchical or mixed regression, and machine learning techniques (Naïve Bayes, Markov Chain, Random Forest etc..)
- Advanced modeling skills with Python and R
- Extensive cloud environment experience, especially GCP and AWS
- Data visualization experience with tools like Tableau, Power BI and Looker a plus
- Understanding of client’s overall marketing objectives and how different media channels support these objectives
- Proven ability to maintain positive client relationships with the ability to diffuse difficult situations and handle escalated client calls/emails with limited oversight.
- Strong communication skills, with the ability to present information in spoken, written or visual form to a variety of audiences, from internal teams to external client executives.
- Ability to multi-task and train others and handle “interruptions”
- Track record of collaboration with teammates, especially overseas team, to share learnings and techniques
· Skilled at managing and coaching challenging employees and client situations.
· Proven ability to bring new solutions, analytical, technical and client-mangement, to the team
This job description is a summary of the essential functions of the job, not an exhaustive or comprehensive list of all possible job responsibilities, tasks, and duties. The responsibilities, tasks, and duties of the jobholder might differ from those outlined in the job description. Other duties, as assigned by the supervisor, might be part of the job.
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