Data Scientist_KAZ-DS-0109-S1

1. Use advanced analytics methods to extract value from business data.

2. Manage the fraud prevention and detection rules in all fraud tools including but not limited to Fraud Guard, EFMS, SAS VI, SAS VA, VRM & FRM.

3. Analyze fraud trends on a periodic basis and provide recommendation to FRM management to implement new fraud prevention & detection controls.

4. Create periodic dashboards and presentations for senior management;

5. Perform large-scale experimentation and build data-driven models to answer business questions

6. Conduct research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence

7. Determine requirements that will be used to train and evolve deep learning models and algorithms

8. Articulate a vision and roadmap for the exploitation of data as a valued corporate asset

9. Influence FRM teams through presentation of data-based recommendations

10. Evangelize best practices to analytics and FRM teams

11. Assemble large, complex data sets that meet functional / non-functional business requirements.

12. Identify, design, and implement internal process improvements: automating manual processes, optimizing analytics delivery, re-designing infrastructure for greater scalability, etc.

13. Build analytics tools that utilize the data to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.

14. Work with stakeholders including the FRM and FMU teams to assist with analytics related technical issues and support their data infrastructure needs.

15. Work with data and analytics experts to strive for greater functionality data systems.

16. Ensure that all data science related work meets data security requirements.

17. Ensure all process of the analytics section of FRM is documented and maintained as an SOP.

18. Maintains relevant documentation to enable peers and other teams to benefit from data science use cases implemented.

- SAS Certified Professional

Email your CV to - [email protected] || Applicants need to send their updated cv, mentioning in the Subject line as - SUBJECT: Applied Position name - Job code (use the job code given in the JD) JOB CODE -KAZ-DS-0109-S1

1. Use advanced analytics methods to extract value from business data. 2. Manage the fraud prevention and detection rules in all fraud tools including but not limited to Fraud Guard, EFMS, SAS VI, SAS VA, VRM & FRM. 3. Analyze fraud trends on a periodic basis and provide recommendation to FRM management to implement new fraud prevention & detection controls. 4. Create periodic dashboards and presentations for senior management; 5. Perform large-scale experimentation and build data-driven models to answer business questions 6. Conduct research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence 7. Determine requirements that will be used to train and evolve deep learning models and algorithms 8. Articulate a vision and roadmap for the exploitation of data as a valued corporate asset 9. Influence FRM teams through presentation of data-based recommendations 10. Evangelize best practices to analytics and FRM teams 11. Assemble large, complex data sets that meet functional / non-functional business requirements. 12. Identify, design, and implement internal process improvements: automating manual processes, optimizing analytics delivery, re-designing infrastructure for greater scalability, etc. 13. Build analytics tools that utilize the data to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics. 14. Work with stakeholders including the FRM and FMU teams to assist with analytics related technical issues and support their data infrastructure needs. 15. Work with data and analytics experts to strive for greater functionality data systems. 16. Ensure that all data science related work meets data security requirements. 17. Ensure all process of the analytics section of FRM is documented and maintained as an SOP. 18. Maintains relevant documentation to enable peers and other teams to benefit from data science use cases implemented. - SAS Certified Professional Email your CV to - [email protected] || Applicants need to send their updated cv, mentioning in the Subject line as - SUBJECT: Applied Position name - Job code (use the job code given in the JD) JOB CODE - KAZ-DS-0109-S1