Director, Analytics (Attribution)
USA - Remote - Maryland, United States
Job Description:
WE WELCOME REMOTE U.S.-based CANDIDATES
Merkle is a leading technology-enabled, data-driven customer experience management (CXM) company. For over 30 years, Fortune 1,000 companies and leading nonprofit organizations have partnered with us to build and maximize the value of their customer portfolios. We are champions for meaningful progress and we strive to be a force for good—for our people, for our clients, for the industry and for our society. We keep our people at the center, creating space for growth, understanding and learning so they can thrive. We embed diversity, in our mindset, in our solutions and in our teams to empower an inclusive, equitable and culturally fluent environment. Building this culture within our teams makes us better collaborators with each other and with our clients, driving better outcomes for all. Merkle is an agency of dentsu.
Job Description
The Director will be an important contributor to our US-based modeling capabilities. Reporting into the Sr. Director, you will use data science techniques to examine marketing activities and to estimate their growth to our clients. These projects will include Media Mix Optimization, Analysis of Covariance (test & control), Cluster Analysis, and Attribution Modeling of disaggregate event-stream data. You will be a “player coach”; in some cases, the Director will lead a team coordinating with some of our most important clients on data acquisition, modeling, and presentation of results on high-visibility projects. In other cases, the Director will be hands-on keyboard revising code and drive innovation. You will manage a US-based and India-based team.
You Will:
Manage data collection with clients
Lead teams to develop reports and processes to manage data quality control
Manage project teams and direct reports effectively to drive innovation in analytics and support client expectations
Oversee and conduct modeling of client data following project timelines
Interpret and visualize model estimates and diagnostics
Deliver insights on model results to senior client leaders
Guide process innovation and continuous improvement
You Have:
A bachelor’s degree in at least one of these fields required: statistics, economics, applied mathematics, optimization, computer science, physics; (preference for an advanced degree)
8+ years of experience applying analytics to measure marketing effectiveness with a focus on measurement and attribution
Experience working with and measuring TV, digital media, and CRM data
Knowledge of statistics/data science, including regression, hierarchical or mixed regression, and machine learning techniques (Naïve Bayes, Markov Chain, Random Forest etc.)
Advanced modeling skills with Python …
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Must be US based Remote
Benefits/PerksContinuous improvement Dental Equal employment opportunities Medical Other benefits Paid Time Off Vision
Tasks- Continuous Improvement
- Deliver insights
- Develop reports
- Drive innovation in analytics
- Interpret and visualize model estimates
- Lead teams
- Manage data collection
- Manage data quality
- Reporting
- Visualize model estimates
Analysis Analysis of covariance Analytics Attribution Modeling AWS BI Cluster analysis Collaboration Computer Science Continuous Improvement CRM Customer Experience Customer Experience Management Data acquisition Data Collection Data Quality Data Science Data Visualization Digital Digital Media Economics GCP Hierarchical regression Innovation Insights Machine Learning Marketing Markov chain Mathematics Measurement Media Media mix optimization Mixed regression Naïve bayes Optimization Power BI Presentation Python Quality Control R Random Forest Regression Reporting Search Statistics Tableau Team Collaboration Technology TV Visualization
Experience8 years
EducationAdvanced degree Bachelor's Computer Science Degree Economics Marketing Master's Mathematics Media Ph.D. Statistics
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9