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Description
Proclivity Systems seeks a Senior Quantitative Engineer to work with its Founder/CEO Sheldon Gilbert on his “Quant Team”
“Sheldon Gilbert is the Founder and CEO of Proclivity Systems. He has a degree in Molecular Biochemistry & Biophysics from Yale University. He is an inventor and innovator in the areas of consumer valuation modeling, high-throughput analytical modeling, and predictive behavioral commerce, Gilbert has multiple patents pending for his system and methodologies”
The Senior Quantitative Engineer will use their background in quantitative analysis and software engineering to build, test and evaluate Proclivity’s quantitative models. To this end they will help maintain massive repositories of data and will be rapidly developing efficient and maintainable quant models. You will be using your quantitative skills in the challenging task of verifying both model implementations and the quality of the models themselves.
Proclivity Systems enables online retailers to execute revenue-generating, direct marketing campaigns based on individual consumer valuations and forecasted willingness to buy. Proclivity gathers all of a retailer's consumer data into its unique Consumer Behavior Bank®, scoring each consumer and generating individual valuations by product or service. The retailer's, marketers and merchandisers use this information to drive highly targeted campaigns through multiple consumer-contact channels, with success metrics in excess of 20% revenue lift and 300% ROI. The Proclivity platform helps retailers retain existing customers and acquire new ones.
The company was recently cited as a dynamic, fast-growing organization by BusinessWeek magazine as one of its Top 50 Tech Start-Ups You Need to Know.
Required Skills and Experience
- Software Engineering: You will work closely with other members of the “Quant Team” to translate needs into solutions.
- Quant Research: You will build quant models to spec, but you may need to improvise to build a prototype model from somebody's whiteboard notes, or to learn enough about a new set of data, a new model, or somebody's process to evaluate it, use it, or test it.
- Product: Pro-actively learning and understanding how our products and services are being used. Working on projects ranging from methodology and technology questions, to new functionality, features and enhancement requests and finally to future business needs and requirements.
- Quality Assurance: You must be willing to test code, models and data. Quality Assurance in Quant Research is challenging and requires analytical thinking, the ability to quickly drill into data to find problems or verify hypothesis, and effective communication.
To learn more about this opportunity, please email an MS Word version of your resume to craig@casearch.net
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