Job description

Are you a Data Scientist looking to join a Data-driven company?


If so I have an exciting opportunity for you! My client whose goal is to help clients and partners grow and thrive through the power of data, analytics, and data-driven solutions are looking for a Data Scientist to join their talented team. Their company model is built on helping companies to understand their customers based on data and insights. The amount of data you will be working with is phenomenal, working with hundreds of thousands of data points within a global company.


In this Role you will support both B2B and B2C initiatives in credit risk space for European markets. In this exciting role, you will bring a mix of advanced analytical skills, credit risk knowledge and client/ stakeholder relationship management to build new insights and analytical solutions that drive company growth. In addition, you will have the chance to utilize credit scoring best practices as well as the latest data science techniques across both supervised and unsupervised machine learning methodologies, while enhancing the visual story telling.


Key Responsibilities:


  • Apply statistical and machine learning concepts to develop supervised and unsupervised models in the area of credit risk.

  • Participate in all aspects of a modelling engagement, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting.

  • Analyse internal raw and structured data, investigate alternate data sources by discovering patterns utilizing data engineering, data mining and visualization methods to support business needs.

  • Research complex business issues and recommend solutions, including model inputs, feature engineering, model design frameworks, and end products that drive innovation for the company.


Key Requirements:


  • Academic university degree in statistics, econometrics, mathematics, computer science, economics and / or civil engineering. Strong academic profile.

  • Good knowledge of Python and SQL, experience in SAS/ SAS Viya could be beneficial.

  • Good hands-on experience of data processing libraries (Python: pandas, numpy, pyspark, etc.), visualization (Python: seaborn, plotly, etc.) and modelling/ machine learning (Python: scikit-learn, xgboost, etc.).

  • 3 years of experience working with statistical models and / or machine learning

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