Senior Data Analytic Manager
About Standard Chartered
We are a leading international bank focused on helping people and companies prosper across Asia, Africa and the Middle East.
To us, good performance is about much more than turning a profit. It's about showing how you embody our valued behaviours - do the right thing, better together and never settle - as well as our brand promise, Here for good.
We're committed to promoting equality in the workplace and creating an inclusive and flexible culture - one where everyone can realise their full potential and make a positive contribution to our organisation. This in turn helps us to provide better support to our broad client base.
The Role Responsibilities
- Work with business stakeholders & domain business analysts to define analytics solution
- Understand their strategies and needs, convert business requirements into analytical problems and implementable data analysis
- Map user requirements to the technology solution and down to components
- Challenge processes (where necessary) to reduce differences to standard operating model
- Design, build, and implement technology analytics solutions appropriate to meet the operational and business/functional requirements defined, and at the same time enforce
- Component Reusability
- Architecture Simplicity
- Process Performance
- Service Maintainability
- Solution Standardization
- Development Traceability
- Strong collaboration with business and other team members
Our Ideal Candidate
- Promote adoption and rollout of Agile and modern software engineering practices;
- Collaborate with other operational, product, technology teams to get the best possible outcome for the bank
- Master or Bachelor Degree in computer science, engineering, math, physics or related fields
- Business English (fluent verbal and written)
- Chinese (fluent verbal and written)
- Proven statistical analysis ability in solving real-world cases
- Proven hands-on experience in analysis of complex data problems
- Proven ability to draw insight, influence others for a common goal in a large organization.
- Proven ability to drive innovative business solutions
- Experience in working with large volumes of data from multiple systems; understand data structure and draw insights. Digital project experience/exposure.
- Good understanding of the Financial products in the retail & wealth management area, engineering (product set up), booking model and process, regulatory backgrounds, valuation. In-depth knowledge of structured or derivatives and securities instruments, the underlying cashflow, valuation, trading and settlement is a plus.
- 10+ years of above experience (Senior Manager)
- 6+ years of above experience (Manager)
Computer Software/Languages/Other Requirements:
- Critical thinking skills
- Must have strong sense of ownership
- Must be an effective communicator with business English literacy, interpersonal, problem solving and analytical skills, and excellent communication and presentation skills
- High learning aptitude, able to learn new products and technology very quickly
- A team player who enjoys working with people on all levels as well as being able to work independently and under pressure to meet tight deadlines
- Quantitative and qualitative analysis skills, classifying, predicting, modeling, forecasting
- Project experience using statistical analysis skills
- Excellent coding skill with Database Query Language (SQL), Java/Python
- Professional level of analytical skills with Microsoft Excel
- Solid experience with BI tools such as SAS, Tableau, Microstrategy, Power BI etc.
- Experience with Hadoop platform, familiar with HiveQL, Spark MLLib. MapReduce, HBase. Hive. Shell scripting.
- Machine learning, deep learning, AI skills/exposure a plus
- Familiar with machine learning classification, regression, clustering and filtering etc.
- Familiar with statistical tests, distributions, maximum likelihood estimators, etc. solid statistics knowledge to understand when different techniques are (or aren't) a valid approach
- Familiar with machine learning methods, i.e.k-nearest neighbors, random forests, ensemble methods, and more. Understand when it is appropriate to use different techniques
Apply now to join the Bank for those with big career ambitions.