Interesting Job Opportunity: Lead/Assistant...
Published date: 2024/01/10
- Location: Ahmedabad, Gujarat, India
1-3 years of experience in ML models in Fraud (Banking domain)
Tool - Well-versed in Python, SQL, excel, PPT
Skillset Requirement
• Hands-on in development of ML models in Fraud specifically in First party Fraud (in context of application fraud would be big plus). Strong foundation in predictive modeling and machine learning along with deep understanding of Fraud risk management. Experience with supervised and unsupervised ML algorithms such as XGBoost, CNN, RNN, SVM, Markov process etc.
Good communication skills
4-10 years of experience in ML models in Fraud (Banking domain)
Tool - Well-versed in Python, SQL , excel, PPT
Skillset Requirement
Hands-on in development of ML models in Fraud specifically in First party Fraud (in context of application fraud would be big plus). Strong foundation in predictive modeling and machine learning along with deep understanding of Fraud risk management. Design ML solutions to address business needs on Fraud side.
Experience with supervised and unsupervised ML algorithms such as XGBoost, CNN, RNN, SVM, Markov process etc. Should be able to synthesize the findings at various points through model development process to share actionable insights with senior leadership and other stakeholders.
Polished and clear communications with senior management.
(ref:iimjobs.com
Tool - Well-versed in Python, SQL, excel, PPT
Skillset Requirement
• Hands-on in development of ML models in Fraud specifically in First party Fraud (in context of application fraud would be big plus). Strong foundation in predictive modeling and machine learning along with deep understanding of Fraud risk management. Experience with supervised and unsupervised ML algorithms such as XGBoost, CNN, RNN, SVM, Markov process etc.
Good communication skills
4-10 years of experience in ML models in Fraud (Banking domain)
Tool - Well-versed in Python, SQL , excel, PPT
Skillset Requirement
Hands-on in development of ML models in Fraud specifically in First party Fraud (in context of application fraud would be big plus). Strong foundation in predictive modeling and machine learning along with deep understanding of Fraud risk management. Design ML solutions to address business needs on Fraud side.
Experience with supervised and unsupervised ML algorithms such as XGBoost, CNN, RNN, SVM, Markov process etc. Should be able to synthesize the findings at various points through model development process to share actionable insights with senior leadership and other stakeholders.
Polished and clear communications with senior management.
(ref:iimjobs.com
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