If the phrase “analytics” or “data science” brings a smile to your face…

If “Monte Carlo” is more than a beautiful gambling destination for the rich and famous…

If you know that “SQL” is not a typo…

…then read on.

Responsibilities

• Advocate, evangelize and leverage our Amp product to create an enterprise analytics library for our customers.
• Enable our customers through teaching, mentoring and coaching to leverage Amp to research, design implement and validate cutting edge analytics to analyze diverse sources of data to achieve desired outcomes.
• Provide expertise on analytics concepts for our customer’s analytics teams and inspire the adoption of enterprise analytics using Amp.
• Provide insight and thought leadership to our customers with regards to building best in class Amp analytic practices.
• Work with business stakeholders to identify business needs and support creation and delivery of the use cases and user stories satisfying those needs.
• Design and lead iterative learning and development cycles.
• Champion the use of data to drive decision making across the company.
• Work closely with clients to solve complex problems involving data analytics.
• Guide clients on how to discover new trends and insights across customers, merchandise and more.
• Pull data, run reports, create segmentations and perform research.
• Creating complex campaign segmentations, trigger based campaigns, troubleshoot data inconsistencies, and help other team members learn and use Amp.
• Create and own the customer insight process through which our clients receive analytical understanding of regarding the business, customer, merchandise, marketing performance and more.

Knowledge and Skills Like

• BA/BS/MS - Stats, Applied Mathematics, Operations Research, Economics, Industrial Engineering.
• Effective communication skills across the organization and at different levels, strategic thinking and actions to influence key stakeholders and business decisions.Ability to advise customers, in clear language, about the implications and value of enterprise analytics.
• Experience working with one or more of the following: R, SPSS, SAS, Python, SQL, HQL, Scala.
• Experience with data query and analysis using the same modeling tools.
• Experience with Data mining, statistical modeling and machine learning. techniques, such as regression, unsupervised learning and decision tree methods
• Knowledge of the principles of statistical analysis, including descriptive and predictive model construction.
• Strong analytical skills with the ability to collect, organize, analyze and disseminate large data sets with attention to detail and accuracy.
• Understand the software development life cycle.
• Basic SQL coding for database analysis; additional programming experience helpful but not necessary.
• 1-5 years’ building descriptive analytics, propensity models, and predictive models working with consumer data.
• Able to explain what the math means to a non-mathematical business person.
• Customer database marketing / customer intelligence /customer relationship management.
• Behavioral targeting.
• Ability to create visual representations of data (using the aforementioned stats tools, plus Excel, PowerPoint, Tableau, and similar).

You may have held titles like:

• Data Analyst
• Consulting and Analytical Solutions Consultant
• Statistical Modeler