Origin CBI, Hill Holliday’s consumer insights group, is looking for an insight technologist – a researcher with solid statistical analysis and programming skills who would be in charge of building and maintaining innovative research tools.
Who We Are
We are a consumer research group at Hill Holliday, a storied advertising agency headquartered in Boston that serves such clients as Dunkin’ Donuts, Bank of America, Chili’s, (RED), LG, TJ Maxx, and many others.
We study how people make choices, and how advertising influences the choices people make. There’s a lot of interesting body of knowledge that goes into it, from economics and sociology to semiotics and evolutionary psychology. The work requires a broad set of skills that have to do with gathering, analyzing, and interpreting many different kinds of data.
One of our big projects right now is developing a new set of methods for evaluating advertising effectiveness (aka copy-testing). It involves measuring the impact of advertising exposure on brand-related memories, approach/avoidance, and choice preferences. We need to make sure that our methodology is as robust as it is innovative; this is where you come in.
Who We Need
The Insight Technologist will:
- Design and build research tools:
- Mechanical Turk tasks in HTML / CSS
- Network analysis and visualization in Gephi
- Data visualizations, either using web libraries or tools such as Tableau
- Data collection and analysis scripts (web scrapers, API requests) in Python or another language
- Automation of research tasks using third-party plug-in tools and APIs (such as meaningcloud.com)
- Plan and execute studies:
- Work with internal and external clients on understanding their business needs. Understand what data needs to be collected, and how to go about collecting it. Design a research strategy.
- Write proposals, design and oversee methodology for data collection and analysis, price out options, line up suppliers.
- Collect data either by designing and programing surveys and experiments (such as discrete-choice conjoints and max-diffs), or by building our own tools to harvest data from online sources.
- Perform rigorous statistical analysis of the results.
- Present the results:
- Separate the important from the merely interesting
- Put the findings in the proper business context
- Make the findings accessible and attractive to broader audiences
- Present the findings to others
A lot of what we do relies on data we collect from social media: from Yelp reviews to inter-connections between Twitter followers of a particular account. We have developed a set of techniques and tools for harvesting, analyzing, and presenting the data. You will continue developing this knowledge.
Often, the data we collect consists of unstructured text, such as open-ended survey responses, or tweets. You will be doing a fair share of manual data coding/categorization. If you can automate it and get it done faster, you can take the rest of the afternoon off.
What It Takes
- Must have:
- Advanced statistics skills: from t-tests and regressions to hierarchical Bayes, latent-class analysis, and Monte Carlo simulations.
- Experience with SPSS, SAS, or R
- Solid programming skills:
- Knowing how to extract and process data with Python and relevant libraries (Matplotlib, Pandas, Flask, Jango), or similar.
- Knowing how to build a simple web app
- Being good at explaining complex things in plain English; confident and clear public speaking
- Disciplined self-directed learning. Being able to pick up new technologies quickly and on your own by reading books and watching video tutorials.
- Awareness of key business principles, interest in consumer and popular culture
- Extra credit:
- Experience with designing and analyzing choice experiments (max-diff, conjoint, discrete-choice, etc), and Sawtooth or similar software
- Knowing how to write VB macros for Excel
- Familiarity with network analysis principles and tools (primarily Gephi)
- A background in experimental quantitative social sciences, cognitive psychology, experimental behavioral economics, or neuro-economics with a focus on choice-making, emotions, motivations, and memory. Experience conducting independent lab research. Basic familiarity with key neuroscience principles.
- Fluency with implicit research methodologies (see millisecond.com)