Quantitative Analyst

Quantitative Analyst

22 Oct
|
FirstRand
|
Sandton

22 Oct

FirstRand

Sandton

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 plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced mathematical models that provide analytical support and interpret insights, to address business opportunities and problems and implement business strategy, with mínimal guidance.

**experience and qualifications**:

- Minimum Qualification - Relevant Degree in Maths, Stats, Engineering, Computer Science, Econometrics, Physics or Actuarial Science






- Preferred Qualification - Honours Degree
- Experience - 3 - 5 years’ experience in a data environment, of which 1 - 2 years ideally at a junior specialist level
- Additional Knowledge - Deep domain knowledge with regards to financial services: Credit, Pricing, Marketing, CVM, Trading etc.
- Design thinking
- Analytics Ops, Agile and SAFe concepts will assist
- Concepts such as: Exploratory data analysis, Data Science Pipeline lines
- 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
- Object-oriented programming
- Big data modelling
- Database management
- Python, SQL, MATLAB, SAS, S-PLUS or R (used for statistical analysis)
- Monte Carlo techniques
- Machine learning
- Data mining and data modelling
- Scala and Spark
- C#/Java,.NET or VBA, Excel
- Mathematical skills






- Calculus (including differential, integral and stochastic)
- Linear algebra and differential equations
- Numerical linear algebra
- 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

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