w******t
发帖数: 471 | 1 Hi, there:
Here we have a risk analytics/modeling position open in Chicago downtown
area. The company is a top consumer lending company in sub-prime area
. We are looking for analytics professional with background in statistics,
SAS, risk modeling (experience preferred but not required.)
Company prefer candidates who already has H1B and may sponsor green card
later. However, if the candidate has good background, we also welcome
candidates who have not applied H1B yet.
JOB DESCRIPTION – Senior Risk Modeling Analyst
POSITION DESCRIPTION
• Provide statistical analytics supports to credit risk, fraud
detection, and other operation in the consumer lending business.
• Develop, implement and monitor regression models in risk management,
fraud detection and marketing.
QUALIFICATION REQUIREMENTS
• Master’s Degree in a quantitative discipline of Statistics or Math
or Bachelor Degree in Statistics or Math.
• Or Bachelor’s Degree in a quantitative discipline of Statistics or
Math or Bachelor Degree in Statistics or Math with 2-6 years’ experience
in
financial risk analysis with 2-6 years of experience in solving analytical
problems using quantitative approaches in the financial industry.
• Experience in advanced analytic tools with SAS and/or R. Certified
SAS Programmer preferred.
• Hands-on experience SQL programming language.
• Experience developing credit risk models in the lending industry.
RESPONSIBILITIES AND DUTIES
• Perform data analysis and develop effective statistical models for
credit risk management, fraud detection, collection, and operation
optimization in consumer lending business.
• Develop and maintain risk models using standard and advanced
statistical techniques - such as logistic regression, multi-nominal
regression, CHAID, and clustering analysis.
• Identify actionable insights, suggest recommendations and influence
the direction of the business by effectively communicating results to cross
functional groups.
• Develop a thorough understanding of business goals and issues,
interpret business needs into data and analytical requirements, and then to
analytical/reporting solutions.
• Evaluate data analysis and model results for communication to
management and working with cross-functional teams to proactively create
business rules, deploy analytics, and manage decisions.
• Develop programs (SQL, SAS, R) to carry out analyses and model
building work.
• Work with other team to implement financial risk management models.
• Work with IT and/or data analytics to plan, develop and improve risk
management data infrastructure.
JOB DESCRIPTION – Risk Modeling Statistician
POSITION DESCRIPTION
• Provide statistical analytics supports to credit risk, fraud
detection, and other operation in the consumer lending business.
• Develop risk management models and strategies.
QUALIFICATION REQUIREMENTS
• Master’s Degree in a quantitative discipline of Statistics or Math
or Bachelor Degree in Statistics or Math with 2-6 years’ experience in
financial risk analysis.
• 2-6 years of experience in solving analytical problems using
quantitative approaches in the financial industry.
• Expertise in advanced analytic tools with SAS and/or R. Certified
SAS Programmer preferred.
• Hands-on experience SQL programming language.
• Experience developing credit risk models in the lending industry.
RESPONSIBILITIES AND DUTIES
• Perform data analysis and develop effective statistical models for
credit risk management, fraud detection, collection, and operation
optimization in consumer lending business.
• Develop and maintain risk models using standard and advanced
statistical techniques - such as logistic regression, multi-nominal
regression, CHAID, and clustering analysis.
• Identify actionable insights, suggest recommendations and influence
the direction of the business by effectively communicating results to cross
functional groups.
• Develop a thorough understanding of business goals and issues,
interpret business needs into data and analytical requirements, and then to
analytical/reporting solutions.
• Evaluate data analysis and model results for communication to
management and working with cross-functional teams to proactively create
business rules, deploy analytics, and manage decisions.
• Develop programs (SQL, SAS, R) to carry out analyses and model
building work.
• Work with other team to implement financial risk management models.
• Work with IT and/or data analytics to plan, develop and improve risk
management data infrastructure | w******t
发帖数: 471 | 2 Hi, there:
Here we have a risk analytics/modeling position open in Chicago downtown
area. The company is a top consumer lending company in sub-prime area
. We are looking for analytics professional with background in statistics,
SAS, risk modeling (experience preferred but not required.)
Company prefer candidates who already has H1B and may sponsor green card
later. However, if the candidate has good background, we also welcome
candidates who have not applied H1B yet.
JOB DESCRIPTION – Senior Risk Modeling Analyst
POSITION DESCRIPTION
• Provide statistical analytics supports to credit risk, fraud
detection, and other operation in the consumer lending business.
• Develop, implement and monitor regression models in risk management,
fraud detection and marketing.
QUALIFICATION REQUIREMENTS
• Master’s Degree in a quantitative discipline of Statistics or Math
or Bachelor Degree in Statistics or Math.
• Or Bachelor’s Degree in a quantitative discipline of Statistics or
Math or Bachelor Degree in Statistics or Math with 2-6 years’ experience
in
financial risk analysis with 2-6 years of experience in solving analytical
problems using quantitative approaches in the financial industry.
• Experience in advanced analytic tools with SAS and/or R. Certified
SAS Programmer preferred.
• Hands-on experience SQL programming language.
• Experience developing credit risk models in the lending industry.
RESPONSIBILITIES AND DUTIES
• Perform data analysis and develop effective statistical models for
credit risk management, fraud detection, collection, and operation
optimization in consumer lending business.
• Develop and maintain risk models using standard and advanced
statistical techniques - such as logistic regression, multi-nominal
regression, CHAID, and clustering analysis.
• Identify actionable insights, suggest recommendations and influence
the direction of the business by effectively communicating results to cross
functional groups.
• Develop a thorough understanding of business goals and issues,
interpret business needs into data and analytical requirements, and then to
analytical/reporting solutions.
• Evaluate data analysis and model results for communication to
management and working with cross-functional teams to proactively create
business rules, deploy analytics, and manage decisions.
• Develop programs (SQL, SAS, R) to carry out analyses and model
building work.
• Work with other team to implement financial risk management models.
• Work with IT and/or data analytics to plan, develop and improve risk
management data infrastructure.
JOB DESCRIPTION – Risk Modeling Statistician
POSITION DESCRIPTION
• Provide statistical analytics supports to credit risk, fraud
detection, and other operation in the consumer lending business.
• Develop risk management models and strategies.
QUALIFICATION REQUIREMENTS
• Master’s Degree in a quantitative discipline of Statistics or Math
or Bachelor Degree in Statistics or Math with 2-6 years’ experience in
financial risk analysis.
• 2-6 years of experience in solving analytical problems using
quantitative approaches in the financial industry.
• Expertise in advanced analytic tools with SAS and/or R. Certified
SAS Programmer preferred.
• Hands-on experience SQL programming language.
• Experience developing credit risk models in the lending industry.
RESPONSIBILITIES AND DUTIES
• Perform data analysis and develop effective statistical models for
credit risk management, fraud detection, collection, and operation
optimization in consumer lending business.
• Develop and maintain risk models using standard and advanced
statistical techniques - such as logistic regression, multi-nominal
regression, CHAID, and clustering analysis.
• Identify actionable insights, suggest recommendations and influence
the direction of the business by effectively communicating results to cross
functional groups.
• Develop a thorough understanding of business goals and issues,
interpret business needs into data and analytical requirements, and then to
analytical/reporting solutions.
• Evaluate data analysis and model results for communication to
management and working with cross-functional teams to proactively create
business rules, deploy analytics, and manage decisions.
• Develop programs (SQL, SAS, R) to carry out analyses and model
building work.
• Work with other team to implement financial risk management models.
• Work with IT and/or data analytics to plan, develop and improve risk
management data infrastructure | s*********h
发帖数: 6288 | | s*********h
发帖数: 6288 | |
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