Chief Methodologist/Statistician
We are interested in a senior level hire (i.e.base of $175 to $225 with a
total compensation between $250k and $300k) to come in and work hands-on
with projects and our team. Eventually, this person would lead the group
and structure a full department around them, but for now it is a very "do
the work yourself" position. We do Segmentation, Positioning and Modeling
for pharmaceutical clients, so they need to be experts in Choice Modeling
and Latent Class Segmentation, as well as Hierarchical Bayesian, etc.
Furthermore, we are sticklers for precision and accuracy so they cannot just
be "idea guys" that want someone else to worry about the details. Also, we
want someone who we can take to clients and help sell/satisfy clients on
projects, this is not just a back-room position. They would need to be in
either Maryland (could work in our office here) or in New Jersey,
Pennsylvania or New York (would work from their home in these locations).
We are a dynamic, fifteen person consulting company.
Candidate must have many of the statistical applications listed below. An
ability/interest in remaining abreast of cutting edge developments in
research skills, such as latent class applications in market research, is
highly desirable. Partnership track potential in this position.
- Discrete Choice Modeling - design of experiments,
multinomial logit models, nested logit models, hierarchical Bayes
estimation, menu models, availability and out-of-stock designs
- Market Segmentation - specialized in latent class models;
experienced in older techniques, including factor/cluster analysis, hybrid
hierarchical clustering, latent trait models, dual optimization segmentation
- Customer Satisfaction and Loyalty - skilled in a variety of
techniques, including factor analysis, linear and logistic regression,
segmentation to analyze and understand customer satisfaction data
- Other tools and techniques - skilled in a wide variety of marketing science methods, including structural equation models, CART, CHAID,
TURF, BundOpt, Maximum Difference Scaling, linear discriminant analysis,
correspondence and canonical discriminant mapping.
Jacqueline Paige
Smith Hanley Associates, Inc.
jpaige@smithhanley.com
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