= lcBodyText.lastIndexOf("";
highlightEndTag = "";
}
if (treatAsPhrase) {
promptText = "Please enter the phrase you'd like to search for:";
} else {
promptText = "Please enter the words you'd like to search for, separated by spaces:";
}
searchText = prompt(promptText, defaultText);
if (!searchText) {
alert("No search terms were entered. Exiting function.");
return false;
}
return highlightSearchTerms(searchText, treatAsPhrase, true, highlightStartTag, highlightEndTag);
}
/*
* This function takes a referer/referrer string and parses it
* to determine if it contains any search terms. If it does, the
* search terms are passed to the highlightSearchTerms function
* so they can be highlighted on the current page.
*/
function highlightGoogleSearchTerms(referrer)
{
// This function has only been very lightly tested against
// typical Google search URLs. If you wanted the Google search
// terms to be automatically highlighted on a page, you could
// call the function in the onload event of your tag,
// like this:
//
//var referrer = document.referrer;
if (!referrer) {
return false;
}
var queryPrefix = "q=";
var startPos = referrer.toLowerCase().indexOf(queryPrefix);
if ((startPos < 0) || (startPos + queryPrefix.length == referrer.length)) {
return false;
}
var endPos = referrer.indexOf("&", startPos);
if (endPos < 0) {
endPos = referrer.length;
}
var queryString = referrer.substring(startPos + queryPrefix.length, endPos);
// fix the space characters
queryString = queryString.replace(/%20/gi, " ");
queryString = queryString.replace(/\+/gi, " ");
// remove the quotes (if you're really creative, you could search for the
// terms within the quotes as phrases, and everything else as single terms)
queryString = queryString.replace(/%22/gi, "");
queryString = queryString.replace(/\"/gi, "");
return highlightSearchTerms(queryString, false);
}
/*
* This function is just an easy way to test the highlightGoogleSearchTerms
* function.
*/
function testHighlightGoogleSearchTerms()
{
var referrerString = "http://www.google.com/search?q=javascript%20highlight&start=0";
referrerString = prompt("Test the following referrer string:", referrerString);
return highlightGoogleSearchTerms(referrerString);
}
Principal Associate - Quantitative Modeler |
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ADD TO JOB CART TO APPLY
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| Job Title: |
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PRINCIPAL ASSOCIATE - QUANTITATIVE MODELER
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Job Description: Job ID(18420) |
Leading financial services firm seeks Quantitative Modelers for its Risk Management division. Successful candidates will partner cross-functionally with business throughout the company to deliver breakthrough analytical solutions to support a winning strategy in a continually changing business environment.
Responsibilities:
Development, enhancement and implementation of statistical and other quantitative models to support loss forecasting, Basel and economic capital calculations, and other business applications
Understanding technical issues in econometric and statistical modeling and applying these skills toward solving business problems
Full ownership of the model development process: from conceptualization through data exploration, model selection and validation, implementation, business user training
Monitoring statistical model performance and providing technical guidance to business leadership
Identifying opportunities to apply quantitative methods to improve business performance
Communicating technical subject matter clearly and concisely to individuals from various backgrounds
Basic Qualifications:
Masters Degree in Econometrics, Statistics, Mathematics or another related field of study
At least 2 years of experience in Statistics or related quantitative field
At least 2 years of experience in Risk Management
At least 1 year of experience in Statistical modeling techniques such as linear regression, logistic regression, decision trees, neural networks, survival analysis
Preferred Qualifications:
PhD in Econometrics, Statistics, Mathematics or other related fields of study
Proficiency in key econometric and statistical techniques (predictive modeling, logistic regression, survival analysis, panel data models, design of experiments, decision trees, data mining methods, and other advanced statistical and econometric techniques)
Experience with very large datasets
Background and experience in consumer or commercial risk, especially scoring, and forecasting models
Authorization for continual employment in the United States
Strong SAS programming skills
Ability to communicate effectively and influence others
Recruiter: Howard Fishman
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| Salary: |
$70 - $105K (based upon experience) |
Location: |
Washington DC suburbs (VA) |
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| Job Categories: |
Consumer Credit/Credit Cards, Risk Management, Statistics/Econometrics |
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