Data Scientist (mid-level) - Machine Learning (NLP) - London/Hybrid - UK Remote options also available - £50-65k + bonus - J12172
Would you like to work for one of the largest and fastest growing credit management services providers in Europe and the market leader in the UK and Ireland? They are looking for a Data Scientist (mid-level) - Machine Learning (NLP) specialist to join their team. You'll develop end to end machine learning based advanced analytical projects related to operational optimisation and improving their customer experience of the company's consumer portfolios.
• Prior experience in working within a team and developing deployable systems in full within agreed deadline.
• Experience of working on various stages of machine learning pipeline, understanding Variance-Bias Trade-off and model development.
• Experience in developing production grade systems and productionising ML models using REST APIs.
• Knowledge of model management and monitoring post deployment.
• Have developed text-based systems employing Natural Language Processing (NLP) algorithms using N-grams, word embeddings and/or transformer-based systems etc.
• Working knowledge of key machine learning based algorithms: supervised (Linear regression, SVM, Random Forests, Gradient Boosting and Neural Networks), Unsupervised (KMeans, Gaussian Mixtures, DBSCAN) etc
• Familiarity with regulations around use of data (CONC, SCORE, principles of reciprocity, GDPR, closed user groups, information security) is a bonus.
• 1-2 years professional experience of developing data intensive software with Python
• Experienced in using SQL to query and process data.
• Cloud computing experience, preferably Azure but AWS is fine too.
• Experience in developing and deploying API services.
• Financial Services on the product or investment side.
• Quantitative degree or post graduate qualifications.
If this sounds like the role for you then please apply today!
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Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website: www.datatech.org.uk