Data Scientist

Локация London
Тип вакансии Business Analysis
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Описание вакансии

Excelian is focussed mainly on the financial services industry. We help our customers maximise efficiency, reduce risk and increase speed of delivery by helping them to adopt better practices and more advanced systems and technology.

Excelian delivers and end-to-end service, from consulting to technology services, complemented by a range of proprietary solutions. Our unique global delivery model is designed to be outstandingly responsive, flexible and focussed on client business priorities. Through it, we deploy dedicated teams made up of the most highly qualified and specialist personnel that bring deep domain knowledge and experience.

Artificial Intelligence and Machine Learning (AI & ML) is revolutionising large parts of the financial services industry. In particular, AI & ML is enhancing customer interactions, increasing revenue, driving down costs, and transforming businesses.

Excelian’s Digital Consulting team is investing heavily in these technologies, and is actively building up a new AI, ML and Analytics Practice – we are therefore looking to hire Data Scientists into our newly-formed London AI & ML team. This will complement our existing Digital Experience, Data Science, Big Data Engineering, Cloud and Grid Computing, and DevOps areas.

The new practice is a start-up environment within a large company – you will be conducting analysis, design and development of prototypes and POCs, using cutting-edge techniques, and with major clients. However, we are not alone – there is an active AI community within the broader Luxoft, focussed on other verticals (eg automotive and healthcare).

We are interested in hearing from individuals with a strong AI & ML background, whether commercial or academic. Deep Learning and associated techniques are of particular interest, as is AI / human interaction.


  • You will work alongside a strong, global team of individuals with diverse backgrounds and skills in analytics and data science to:

o Analyse, design and develop AI & ML prototypes and proof of concepts

o Identify and ingest data sources, whether internally or for clients, and perform feature engineering for integration into models

o Build analytical data models on ML platforms, to successfully realise client goals

  • You will assist the practice in:

o developing practice thought leadership materials

o participating in pre-sales work and client work as necessary

o discovering and verifying opportunities for new business

o helping to structure work, planning new analyses, translating business questions into analytical projects

  • You will collaborate with business and technology partners to evaluate techniques, data sources and tools to grow and develop the data science practice



  • Strong modelling skills – neural networks, multivariate analysis (MVA), time series, regression and nonlinear models, support vector machines, and similar
  • Post-graduate degree in Mathematics, Statistics, Engineering, Computer Science, Computational Statistics, Physics, Operations Research or other similar quantitative field
  • At least three years of experience in data science, in particular in designing, developing, validating, and deploying predictive models
  • Experience with advanced Machine Learning techniques including neural networks, deep learning, and reinforcement learning, as well as a background in more classic techniques such as support vector machines, principal component analysis, regression, time series analysis and clustering
  • Hands-on experience applying machine learning techniques using packages such as scikit-learn, TensorFlow, Keras, Theano, and DSSTNE
  • Solid engineering and scripting skills in one or more of Python, R, SAS, Matlab and SPSS
  • Excellent analytical skills
  • Strong communication and presentation skills, both verbal and written. The successful candidates will be expected to communicate effectively with both business and technical teams


  • Experience in using mainstream languages to acquire, clean, and model large data sets.
  • Experience in visualizing and communicating data using tools such as Qlik, Tableau, or packages d3.js, and Seaborn.
  • Good understanding of sourcing and wrangling data from warehouses, Big Data (e.g. Hadoop, Spark) and other sources using SQL and scripting
  • Experience in the analysis of large, complex, multi-dimensional data-sets with a variety of analytical methods
  • Experience in projects involving cross-functional teams

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