向国内邮寄药品# PennySaver - 省钱一族
t*9
1 楼
印度人顾问公司，但好处是当data science第一人，和入职后直接跟大银行做，
project已谈好。现在就要人，有兴趣的朋友可以试试。MS/PhD 加四年经验。
-Need for a data scientist in NYC to build some scorecards for a lending
business
-The person should have knowledge of consumer lending, credit bureaus and
predictive modeling.
-Developing data-drives decision to build consumer credit origination/
underwriting scorecards.
· Work with the teams to build the credit scoring, pricing, and risk
scorecards
· Implement and test data-mining projects on our large data repositories.
· Develop and test regressions, clustering, and classifiers in order to
zero in on statistically-significant conclusions.
· Design and implement machine-learning classifiers
· Design and implement time-efficient optimization algorithms to increase
accuracy and throughput.
· Collaborate with other teams in developing production Python code.
· Make presentations on key findings to management
·
Basic Qualifications
– Advanced degree (PhD or Master’s) in quantitative disciplines like
Mathematics, Statistics, Engineering or computer science
– Hands-on experience with multivariate analysis, statistical models, time
series analysis, clustering in financial services or related industry
– Prior modeling experience in credit risk, marketing response modeling and
forecasting required
– Machine learning knowledge including neural networks, support vector
machines, random forest highly desired
– Strong familiarity on dealing with large data sets in a Big Data
environment
– Experience with one or more of the industry standard modeling tools (SAS,
R, Python)
– Ability to explain complex statistical models and analysis to drive
business ideas
– Strong project management skills and a track record building or leading
decision science function
– Experience working in a start-up business or a new business line within a
larger organization
project已谈好。现在就要人，有兴趣的朋友可以试试。MS/PhD 加四年经验。
-Need for a data scientist in NYC to build some scorecards for a lending
business
-The person should have knowledge of consumer lending, credit bureaus and
predictive modeling.
-Developing data-drives decision to build consumer credit origination/
underwriting scorecards.
· Work with the teams to build the credit scoring, pricing, and risk
scorecards
· Implement and test data-mining projects on our large data repositories.
· Develop and test regressions, clustering, and classifiers in order to
zero in on statistically-significant conclusions.
· Design and implement machine-learning classifiers
· Design and implement time-efficient optimization algorithms to increase
accuracy and throughput.
· Collaborate with other teams in developing production Python code.
· Make presentations on key findings to management
·
Basic Qualifications
– Advanced degree (PhD or Master’s) in quantitative disciplines like
Mathematics, Statistics, Engineering or computer science
– Hands-on experience with multivariate analysis, statistical models, time
series analysis, clustering in financial services or related industry
– Prior modeling experience in credit risk, marketing response modeling and
forecasting required
– Machine learning knowledge including neural networks, support vector
machines, random forest highly desired
– Strong familiarity on dealing with large data sets in a Big Data
environment
– Experience with one or more of the industry standard modeling tools (SAS,
R, Python)
– Ability to explain complex statistical models and analysis to drive
business ideas
– Strong project management skills and a track record building or leading
decision science function
– Experience working in a start-up business or a new business line within a
larger organization
