Staff Scientist - Fraud Modeling

Job description

Overview

 

 

SAS believes in the whole employee experience. Meaningful work. Empowerment to make a difference that changes people’s lives. Dynamic work environments that foster innovation. And an award-winning culture that makes it all possible. We believe great ideas can come from anywhere. Whether you're a university recruit, or an experienced professional ready for the next big challenge, SAS brings perks, passion, and the potential to grow. No limits.

 

 

 No matter the industry, organizations are collecting data at a faster pace than they can often handle. SAS provides everything they need to make sense of that data, manage its growth and determine what information brings the most value. Whether it’s to reduce fraud in banking, speed drugs to market in life sciences, forecast demand in retail, detect security breaches in government or identify students at risk of falling behind, SAS takes pride in making a difference.

 

 

Position Location = San Diego, CA - SAS Regional Office.

 

You will work from the SAS office in San Diego, California. As a member of the analytics team, you will analyze customer data and build high-end analytical models for solving high-value business problems, such as credit and debit card fraud, online banking fraud, credit risk, network security, etc.  Duties include:

·  Processing and analyzing large volumes of (customer) data
·  Building predictive models with advanced machine learning algorithms such as Neural Networks, Decision Trees, Boosting/Ensemble methods, Clustering, Online learning, etc
·  Interacting with customers from the data analysis stage to the final report presentation
·  Assisting in technical sales support as needed
·  Constantly innovating by building new variables; improving modeling techniques to boost model performance; maintaining and refining the processes and procedures for building high-end analytic modeling solutions
·  Writing coherent reports and making presentations on high-end analytical projects
·  Leading a group of scientists through project completion as needed

Essential Requirements:

·  Master's degree in statistics, mathematics, computer science, engineering, or the physical sciences
·  At least 2 years related experience such as analyzing data and/or building analytical models; in either an academic or professional setting
·  Good programming skills with knowledge of multiple operating systems (e.g. Unix/Linux), scripting languages (e.g. Bash, Perl, Python) and the ability to deal with very large volumes of data
·  Ability to communicate with people of various technical and business backgrounds, including the ability to explain difficult technical concepts in simple terms to business users
·  Thorough knowledge of at least some supervised and unsupervised modeling techniques such as Logistic/Linear Regression, SVMs, Neural Networks / Deep Networks, Boosting/Ensemble methods, Decision Trees, Clustering, etc

Additional Requirements:

·  Excellent written and verbal communication skills
·  Ability to think analytically, write and edit technical material, and relate statistical concepts and applications to technical and business users
·  Ability to work independently and with a team environment
·  Ability to travel as business requirements dictate

Preferences:

·  Ph.D. in applied statistics, mathematics, computer science, engineering, or the physical sciences
·  Industry experience in mathematical/statistical modeling, pattern recognition, or data mining/data analysis
·  Extensive experience specifying and building advanced analytic solutions for the financial services and related industries with large-scale transaction data
·  Extensive experience in data management, deployment and product support for advanced analytic solutions
·  Excellent programming skills and knowledge of SAS and scripting languages
·  Ability to translate model performance to financial benefit for the business by incorporating knowledge of customer business practices.

 

 

To qualify, applicants must be legally authorized to work in the United States, and should not require, now or in the future, sponsorship for employment visa status.

SAS is an equal opportunity employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other characteristic protected by law.

The level of this position will be determined based on the applicant's education, skills and experience.

Resumes may be considered in the order they are received.

SAS employees performing certain job functions may require access to technology or software subject to export or import regulations. To comply with these regulations, SAS may obtain nationality or citizenship information from applicants for employment. SAS collects this information solely for trade law compliance purposes and does not use it to discriminate unfairly in the hiring process.

 

Want to stay up to date with SAS culture, products and jobs? Follow us on LinkedIn