If the phrase “customer database marketing / statistical behavioral analytics” 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 we'd like to talk with you about joining our team.
The high-level job description is simple: design, construct, and implement advanced customer data analytic models. The devil, as they say, is in the details and that’s where you come in. Worry not, though, because you will learn a lot from us - we've developed some very unique IP - and we'll learn a lot from you!
You May Have Held Titles Like:
- A champion for the use of data to drive decision making across the company.
- A professional who works closely with clients to solve complex problems involving data analytics
- Excited about comparing customer behavior by channel to help improve marketing and merchandising efforts.
- Curious and passionate about data and discovering new trends and insights across customers, merchandise and more
- Proficient in pulling data, running reports, creating segmentations and performing research.
- Capable of creating complex campaign segmentations, trigger based campaigns, troubleshooting data inconsistencies if they arise, and helping other team members learn and use the system to whatever degree is needed.
- Can create and own the customer insight process through which our clients receive analytical understanding of regarding the business, customer, merchandise, marketing performance and more.
- Experienced in building and managing a high performing, analytical team that supports and pushes the business to excel.
- Skilled at analyzing demographic and psychographic variables to develop customer profiles.
You Have Knowledge and Skills Like: Junior level:
- Data Analyst
- Director of Customer / Retail Insights and Analytics
- Director, Consulting and Analytical Solutions
- Senior Analyst
- Statistical Modeler
Intermediate level - all of the above plus:
- BA/BS/MS - Stats, Applied Mathematics, Operations Research, Economics, Industrial Engineering
- Knowledge of the principles of statistical analysis, including descriptive and predictive model construction.
- Relevant internship or research project experience with end-consumer analytics using large databases (at least 1MM rows).
- Statistical modeling with SAS, SPSS, R, or equivalent.
- Database analysis using the same modeling tools.
- Basic SQL coding; additional programming experience helpful but not necessary.
Senior level - all of the above plus:
- 3-5 years’ additional experience 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.
- Evidence (via specific project examples) of innovative application of analytic techniques to solve hairy problems.
- Experience building models with large data bases of consumer activity - POS transactions, online transactions, loyalty program activity, email open/click-through.
- Call center, customer survey, or other semi-structured data analytics.
- 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).
- An additional 3-5 years of experience leading teams of analysts performing all these tasks.
- Solid understanding of the principles, strengths and shortcomings of a wide range of analytic techniques, including regression (in its multiple forms), time series analysis, Monte Carlo simulation, clustering and segmentation techniques (including K-means), simulation modeling, multi-objective optimization techniques (including simplex), and so on.
- Ability to teach and explain - both technical and business. The ideal candidate is equally comfortable training more junior members of a team how to apply these various complex formulations to solving a problem, and explaining the business meaning of those complex formulations to senior executives.
- Online data analytics (SEM, display ad click through, etc.).
- Social and/or text analytics.
- Analysis of mobile shopping or mobile application activity.
Aginity - 17 months ago