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VP / AVP, Data Scientist, Group Finance Corporate Treasury, Group Finance

Singapore, Singapore | DBS Bank

  • Industry:
    Banking / Investment Banking
  • Position Type:
    Full-Time
  • Functions:
    Accounting / Control
    Financial Services Professional
    IT / Information Technology
    Biotech/R&D/Science
  • Experience:
    3-5 years
    5-7 years
Job Description:
54 people have viewed this job

To design and develop algorithms/models for addressing specific business problems around the areas of Balance Sheet and Capital Management


To explore and build up long term capabilities in various domains such as reinforcement learning, stochastic optimization, Bayesian frameworks, deep learning and machine learning


To partner with business leads to identify opportunities for collaboration and development of analytics solutions


To operationalize algorithms/models into re-usable libraries for the team


To automate the algorithms/models by leveraging on existing tools and frameworks


Requirements 


Curious individual that has a strong interest in exploring various technical domains in the areas of analytics and data science.


3-7 years of experience in applied statistical learning, machine learning and data science with tangible outcomes.


Academic background with industrial research experience will be strongly preferred.


Excellent written and communication skills, especially one who can explain complicated models and simplify them.


A keen learner who desires to learn and acquire new knowledge both in business and technical domains, as well as to acquire proficiency in new tools, languages and techniques.


A strong team player who can contribute as an individual, while being a mentor to other team members through sharing of knowledge.


Extremely proficient in Python development, with in-depth knowledge of libraries such as Scikit learn, TensorFlow, PyTorch, Keras


Proficient in software development, especially in big-data tools such as Spark, Hive etc.


Qualifications:


Master’s or PhD in Computer Science, Statistics, Math, Engineering or other quantitative disciplines


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