• Competitive
  • Singapour, Singapore
  • CDI, Plein-temps
  • OCBC Bank
  • 22 oct. 17

AVP, Data Scientist (Data Analytics)

AVP, Data Scientist (Data Analytics)

1. Analyse and visualize key trends within large datasets
2. Use strong business acumen, as well as an ability to communicate findings, and mine vast amounts of data for useful insights
3. Use a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems
4. Use insights to influence how an organisation approaches business challenges
5. Build and deploy Machine Learning Algorithms, Advanced Analytics, and Data Visualization
6. Be a critical member of key data science projects spanning multiple areas including Financial Crimes and Compliance, Risk Management, MIS, HR and Marketing
7. End-to-end project management and feedback to users using agile techniques
8. Educate the broader community on data analytics through structured training programs and other outreach initiatives
9. Partner with assigned teams and/or business units to provide deep expertise and advisory on data analytics needs
10. Strong knowledge of data architecture to ensure analytics objectives are aligned to Technology Architecture

Qualifications
1. 3-6 years of work experience in the field of analytics and data science, with 2+ years' practical experience with SAS, ETL or data processing
2. At least two years data analytics working experience, preferably in banking
3. Ability to deal with data is different formats - Files, RDBMS (Teradata, Oracle etc.), Logs, Websites etc.
4. Min Degree in Statistics, Mathematics, Data or Computer Science or a related field
5. An analytical mind and team player to build strong business partnerships
6. A strong communicator, with clear articulation of analytical findings through presentations. Experience with data visualization packages will be a plus
7. Innovative and Agile thinking
8. Understand NLP, machine learning, deep learning, data mining, algorithmic foundations of optimization.
9. Experienced with common data science toolkits, such as R, SAS, Python or Spark-ML. Excellence in at least one of these is highly desirable
10. Great communication skills
11. Experience with data visualisation tools, such SpotFire or QlikView
12. Interested to acquire new tools as SQL, Spark, Hive, Pig for Data preparation
13. Experience with NoSQL databases, such as HBase .
14. A data lover and constantly looking at innovative solutions to further improve data analytics capabilities
15. Confident dealing with people at all levels of the organisation
16. Good communication skills, articulate and innovative to engage stakeholders
17. Good team player, but able to work independently with minimal supervision in a challenging and fast moving environment
18. Confident working in cross-functional, collaborative environments
*LI-EL