Data Scientist I

About us, purpose, experience and qualifications
**about us**:
- make a promise
- be deeply invested
- value our differences
- build trust, not territory
- have courage
- always do the right thing
**purpose**:
- To build, optimise and implement innovative quantitative analytical methodologies, procedures, and advanced mathematical models that provide analytical support and interpret insights, to address business opportunities and problems and implement business strategy, under guidance against predicted results and deliver according to set processes and procedures**experience and qualifications**:
- Minimum Qualification - Relevant Degree in Maths, Stats, Engineering, Computer Science, Econometrics, Physics or Actuarial Science
- Experience - 1 to 3 years’ experience in data environment
- Additional Knowledge - Domain knowledge with regards to financial services:
Credit, Pricing, Marketing, CVM, Trading etc.
- Design thinking
- Analytics Ops, Agile and SAFe concepts will assist
- Hands on experience using model such as:
Naïve Bayes, Support Vector Machines, Classifications, Boosting Algorithms, Time Series, Feature Engineering and
- Dimensionality Reduction
- Data and Information Management topics e.G. structure, dimensions, storage
- Database management
- Python, SQL, MATLAB, SAS, S-PLUS or R (used for statistical analysis)
- Monte Carlo techniques
- Machine learning
- Data mining and data modelling
- C#/Java,.NET or VBA, Excel
- Calculus (including differential, integral and stochastic)
- Linear algebra and differential equations
- Probability and statistics
- Game theory
- Portfolio theory
- Equity and interest rate derivatives, including exotics
- Systematic and discretionary trading practices
- Credit-risk products
- Financial modelling Data visualisation and reporting