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.
Deliver Data Science analysis to support business decisions for various Business Units of the Bank. Develop Advanced Analytics components to be included in innovative applications by creating prototypes and developing solutions based on advanced analytics, leveraging internal data sources as well as investigating the potential of external data sources.
Train Predictive and Machine Learning models 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, building and optimizing classifiers using machine learning techniques
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
Build Prototypes to demonstrate the derive actionable insights from data, as part of Agile teams
Work with Data Engineers to define data requirements and review recommended architecture
Program advanced analytics capabilities and algorithms to be included in new business solutions.
Develop visualization interfaces that help business make more insightful decisions
Maintain cutting edge in Data Science
Take initiative in evaluating new approaches from data science research
Test new tools and packages
Support the programs for changing the business culture towards more data driven
Identify, profile, analyze and present the data discovery output for analytic projects
Develop data ingestion pipeline and create the analytic data assets for analytic projects
Work with data engineer to enhance the analytic data infrastructure and develop enterprise analytic data mart
Perform data wrangling and feature engineering for machine learning
Create helper functions to automate frequently encountered wrangling and feature engineering tasks
PhD/Masters/Bachelors in Computer Science, Statistics, Applied Mathematics, Operations Research, or related disciplines.
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
Good applied statistics skills, such as distributions, statistical testing, regression, etc.
Highly proficient with data wrangling, analytic, transformation and feature engineering using programming tools such as Spark, Python or R. Excellent knowledge of SQL.
Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc .
Experience with data visualisation tools, such as D3.js, GGplot, etc.
Proficiency in using query languages such as SQL, Hive, Pig
Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
Good scripting and programming skills (Python, Java, Spark...)
Experience with commercial Analytics packages is a plus (Teradata, SAS, Qlikview...)
Practical experience in following domains, in addition to Machine Learning, is a plus: Natural Language Processing, Deep Learning, Time Series, Web/Log Analysis, Streaming Data Analysis, Geospatial Analysis
Great communication skills
Excellent communication and presentation skills in English.
Taste for working in teams, self-starter, able to work on multiple projects in parallel
At least 3 years of industry experience in data analytics working in a big data environment
Experience working in multi-cultural environments
We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.
Internal Number: 5840908
About DBS Bank Limited
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