6 of 6 Statistical Inference Jobs in the UK

by business stakeholders, the model risk function, and other groups. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience. Experience in statistical inference and experimental design (such as probability, linear algebra, calculus). Data wrangling: understanding complex datasets, cleaning, reshaping, and joining messy datasets using Python. Practical expertise and work More ❯

years of professional working experience Someone who thrives in the incremental delivery of high quality production systems Proficiency in Java, Python, SQL, Jupyter Notebook Experience with Machine Learning and statistical inference. Understanding of ETL processes and data pipelines and ability to work closely with Machine Learning Engineers for product implementation Ability to communicate model objectives and performance to business More ❯

to design and deploy machine learning services that are accessible via APIs for use in GUIs or direct access. Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by More ❯

to design and deploy machine learning services that are accessible via APIs for use in GUIs or direct access. Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by More ❯

Regulatory) Corporate credit risk models (IRB, PD/LGD/EAD) Competencies: Essential: Good background in Math and Probability theory - applied to finance. Good knowledge of Data Science and Statistical inference techniques. Good understanding of financial products. Good programming level in Python or R or equivalent. Good knowledge of simulation and numerical methods Awareness of latest technical developments More ❯

Regulatory) Corporate credit risk models (IRB, PD/LGD/EAD) Competencies: Essential: Good background in Math and Probability theory - applied to finance. Good knowledge of Data Science and Statistical inference techniques. Good understanding of financial products. Good programming level in Python or R or equivalent. Good knowledge of simulation and numerical methods Awareness of latest technical developments More ❯