Analyst, Junior Data Scientist, Analytics Centre of Excellence, DBS Group Transformation
Here at the DBS Transformation Group, we focus on nurturing the culture of the "World's Best Digital Bank" (Euromoney, 2016 & 2018) and Best Bank in the World (Euromoney 2019). Our approach is a combination of both science and art; we immerse our stakeholders in the world of design thinking and experimentation, drive rigorous creativity along our pipeline, and build connections between corporate entrepreneurs and start-ups. We are a cross-disciplinary team focused on the invention of solutions that will radically improve the way people live, work and play. We are passionate and committed to making banking joyful (while having lots of fun)! DBS's transformation has been recognised by HBR as one of the top ten transformations of the decade alongside the likes of Netlflix, Amazon, Microsoft. The philosophy of lean and agile and underpinned the success and the need to continually drive our agile capability is essential if we are to continue our transformation journey. Job Purpose
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, analyse 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
- 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
- Data-oriented personality
- Excellent communication and presentation skills in English.
- Taste for working in teams, self-starter, able to work on multiple projects in parallel
- At least 1 year 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.