Senior Data Science Model Validator

Key Skills

Java Programming, Oracle, Python Programming, SQL, Apache Hadoop, Scala Programming, R Programming, SPARK Programming, SAS

Job Description

• You have a PhD or MSc degree in Mathematics, Physics, Econometrics, Quantitative Finance, Data Science or related field,
• You have at least 5 years of experience in model development, validation or model risk management,
• You have a passion for data science as applied in the banking sector,
• You have a thorough understanding of the machine learning algorithms and tooling and are able to pass your knowledge to others,
• You know how to build and validate multiple Machine Learning methods: Classification, Regression, Clustering, Unsupervised methods, Text Mining,
• You have an excellent understanding of Random Forests, Gradient Boosting, Neural Networks, Logistic Regression, SVM, KNN, K-Means, etc,
• You have experience in Python, R, Scala, SAS or other data science tools and platforms,
• You have an excellent English verbal and writing skills,
• You are enthusiastic, communicative, flexible and you are a team player,
• You are transparent, open-minded and value diversity and inclusion.

English level - C1.
You'll get extra points for:

• Experience with the agile way of working and interests in progressing with this
• Transparency, open-mindedness and value for diversity and inclusion
• Knowledge in Parametric and non-parametric statistics is a pre.
• Knowledge in data processing Tools: Spark, Hadoop, Oracle, SQL
• Being an advocate of the “ING Orange Code”, a naturally collaborative person and team player

Working time per task:

• Technical review of the models assessing the conceptual soundness and developmental evidence of a model - 40
• Review of compliance with regulations and internal policies by performing quantitative analyses and independent testing - 20
• Writing detailed validation reports, including a model risk assessment and a description of the validation findings - 10
• Interact with stakeholders including model developers, senior management, ECB and other regulators, and internal & external audit - 10
• Keep track of new developments in data science and applicable regulation - 10
• Contribute to the continuous improvement of methodologies, standards and automation - 10