AVP / Senior Assoicate, Data Scientist, Core System Technology, Technology and Operations
- Permanent, Full time
- DBS Bank Limited
- 22 Sep 17
See job description for details
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.
- Train predictive and machine learning models to support business challenges.
- Perform ad-hoc exploratory analysis and data mining tasks on diverse datasets from small scale to “big data”
- Select features, build and optimize classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Extend company’s data with third party sources of information where relevant
- 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
- Build prototypes to derive actionable insights from data.
- Work with data engineers to define data requirements and review recommended architecture
- Develop advanced analytics capabilities and algorithms to be included in new business solutions.
- Develop visualization interfaces and dasboards to support businesses in making insightful decisions
- Maintain cutting edge in the practice of data science
- Take initiative in evaluating and practising new approaches from relevant research
- Test and evaluate new tools and packages
- Support the organization in transformation towards a data driven business culture
- 2-6+ years in data science related roles
- Experience working in multi-cultural environments
- PhD/Masters/Bachelors in Statistics, Computer Science, Applied Mathematics, Operations Research, or related disciplines.
- Excellent understanding of machine learning techniques and algorithms, comprising supervised, unsupervised learning techniques such as k-NN, Naive Bayes, SVM, Decision Trees, Cluster Analysis etc.
- Good applied statistical analysis skills, such as distribution theory, statistical testing and linear models etc.
- Core experience with data science toolkits (R, RStudio, SKLearn etc)
- Good scripting and programming skills (Python, Scala, R etc)
- Proficiency in using query languages (SQL, Hive, Pig etc)
- Familiarity with Big Data stacks (e.g. Hadoop, Spark technologies)
- Experience with NoSQL databases (MongoDB, Cassandra, HBass etc) is a plus
- Experience with commercial analytics softwares and packages (Teradata, SAS, Qlikview etc) is a plus
- Practical experience in one of the following domains, in addition to machine learning, is preferred: Natural Language Processing, Deep Learning, Time Series, Web/Log Analysis, Streaming Analytics, Geospatial Analysis
- Data-oriented personality
- Excellent communication and presentation skills in English.
- Team player, self-starter, ability to work on multiple projects in parallel is necessary
We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.