BNP Paribas - Analyst - Quant (2-5 yrs)

Quant Analyst

Responsibilities:

- Apply mathematical and statistical techniques to economic and financial market data, producing pattern recognition, relationship identification and time-series model projections.

- Develop libraries and leading quant indicators for asset prices, economic variables and derivative markets.

This entails:

- Maintaining existing libraries and developing new modules.

- Running data analytics.

- Exploring use of new data science techniques.

- Testing new date sets (i.e. alternative data).

- Develop tools for data managing for model outputs/inputs.

- Maintain and update models, including creating visual representations of outputs, compiling of dashboards, presentations and publications.

- Work with other teams for the improvement of digitalization, automation and distribution of contents.

- Support the Macro Quant & Derivative Strategists (located in London and Portugal) in the process of researching new modelling techniques and producing thematic research reports, which relate quant analytics to the current economic and market news flow.

Profile And Skills To Success:

- Graduate in a numeric subject (e.g.: Computer Science, Applied Maths, Engineering, Physics, Economics with a speciality in Econometrics, Finance).

- Experience with Object oriented programming is a must. Past experience in designing libraries/modules is a plus.

- Ability to demonstrate elementary knowledge and/or interesting in financial markets.

- Strong interest in software development, data analysis and solid analytical skills.

- Ability to write robust code in Python or other coding language.

- Familiarity with machine learning and statistical models libraries, like 'scikit-learn' and 'statsmodels'.

- Knowledge of principals of classical machine learning models (linear regression, SVMs, k means clustering, PCA, decision trees) Knowledge in basic neural networks is a plus.

- Up to 2 years of experience in a similar role.

- High attention to detail / rigor.

- Autonomy, proactiveness, reliability and results driven.

- Critical thinking, creative approach to problem solving.

- Strong communication skills (both spoken and written).

- Fluency in English.