DBS - Data Scientist

Location: Singapore
Business sector: Data Engineering with Machine Learning Fundamentals
Job reference: 543556
Published: 4 months ago
Group Technology and Operations (T&O) enables and empowers the bank with an efficient, nimble and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation. In Group T&O, we manage the majority of the Bank's operational processes and inspire to delight our business partners through our multiple banking delivery channels.

What You'll Be Doing 
  • Build machine learning solutions to solve various business questions.
    • Perform ad-hoc exploratory statistics and data mining tasks on diverse datasets from small scale to big data
    • Select features, build and optimize classifiers using machine learning techniques
    • Perform data wrangling and feature engineering
    • Data mining using state-of-the-art methods
    • Extend company’s data with third party sources of information when needed
    • Enhance data collection procedures to include information that is relevant for building analytic systems
    • Process, cleanse, and verify the integrity of data used for analysis
    • Carry out ad-hoc analysis and present results in a clear manner
  • Maintain cutting edge in data science
    • Take initiative in evaluating new approaches from data science research
    • Test new tools, platforms and packages
    • Support the programs for changing the business culture towards more data driven decision making
    • Create helper functions to automate frequently encountered wrangling and feature engineering tasks

Skills You'll Need

  • Masters or Bachelor Degree in Computer Science, Statistics, Applied Mathematics, Operations Research, or related majors.
  • With industry experience in data science/machine learning projects working in a big data environment
  • Industry experience in NLP, search, recommendation systems, time series modelling is a plus.
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Random Forests, XgBoost etc.
  • Familiar with sklearn
  • Highly proficient with data wrangling and feature engineering
  • Familiar with programming tools such as Spark, Python and SQL.
  • Great communication and presentation skills
  • Data-oriented personality and able to multi-task