Associate, Data Analyst, Operations Intelligence, Data Science, SG Consumer Banking Operations, Technology and Operations
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. Operations Intelligence (OI) under SG Consumer Banking Operations, enables Operations to make data-driven decisions for proactive management of service, productivity, and risk. Responsibilities
- Collaborate with cross-functional teams/stakeholders to identify opportunities, gather requirements and prioritize actionable insights through application of Machine Learning (ML) /Deep Learning (DL) Models to solve complex problems for proactive management of service, productivity, and risk.
- Responsible for full AI/ML model life cycle management, industrialisation and operationalisation including data gathering, development, model training, deployment, monitoring and performance optimization using ADA platform and tools.
- Closely partner stakeholders to design experiments, perform data iterations and present/share the results of the data with relevant stakeholders (e.g. Management, squad members) in an easily digestible format.
- Provide analytics support for different purposes such as managing digital exceptions during production issues, improving productivity and mitigating risks.
- Good Business knowledge in 'connecting the dots' from the data to solving business problems using, but not limited to, classification, regression, clustering and deep learning algorithms
- Ability to understand the business operations as a whole and translate questions into effective analysis
- Innovate to deal with data imperfections; data munging and using algorithms to efficiently organize large data sets.
- Design and build automated reporting dashboards on our data visualization platforms
- Minimally University degree in mathematics, applied statistics, data mining, machine learning, computing or related quantitative discipline with a strong background in statistical concepts and calculations
- At least 2 years of experience in model development, validation and testing, deployment and model performance monitoring.
- Good understanding of statistical and predictive modelling concepts, machine learning approaches, NLP concepts and deep learning
- Strong programming and modelling skills in the following:
- Python, Pyspark, Spark SQL, MySQL
- Hadoop eco-system (Hive, HDFS, Pig etc.)
- Data engineering pipeline experience including real time data computation
- End to end data science workflow experience, starting from data extraction, wrangling, modelling and deployment in production environment
- Deep and practical understanding on implementing high performance, well-behaved analytics applications; data ingestion, feature engineering, model selection, training, validating and deployment
- Experience manipulating structured and unstructured data sources for analysis
- Familiar with the use of Qlikview/ Tableau for both development and insights reporting.
- Business Knowledge or prior experience in the consumer banking area would be advantageous
Requirements (Nice to have)
- Strong combination of analytical skills, intellectual curiosity, and with a strong appetite for challenges
- Highly adaptable with big data technologies, able to pick up new methods and techniques quickly and apply towards solving a problem at hand
- Comfortable working in a fast paced, hypothesis driven, collaborative, and iterative engineering environment
- Comfortable deconstructing complex/open-ended problems which may not yield a clear-cut solution
- Meticulous and structured individual with good time management to oversee/ manage or prioritize multiple deliverables
- Integrity and maturity to manage the sensitivity of data
- Excellent written and verbal communication skills
- Good team player with the ability to work collaboratively as part of a squad while maintaining the ability to work independently in carrying out tasks to completion aligned to original goals with minimal supervision
- Experience on Cloud computing platform.
- Experience on Data Science Workbench (Cloudera, AWS)
- Exposure to McKinsey's problem solving techniques, analytics translator.
We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.