Bright minds,
sharp solutions

Luxoft is a global IT service provider of innovative technology solutions that delivers measurable business outcomes to multinational companies. Its offerings encompass strategic consulting, custom software development services, and digital solution engineering. Luxoft enables companies to compete by leveraging its multi-industry expertise in the financial services, automotive, communications, and healthcare & life sciences sectors. For more information, please visit the website.

Line of Business:

Financial Services

Position:

Data Scientist

Project Description

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.

Responsibilities

Responsibilities
You will work alongside a strong, global team of individuals with diverse backgrounds and skills in analytics and data science to:
◆ Analyse, design and develop AI & ML prototypes and proof of concepts
◆ Identify and ingest data sources, whether internally or for clients, and perform feature engineering for integration into models
◆ Build analytical data models on ML platforms, to successfully realise client goals
You will assist the practice in:
◆ Developing practice thought leadership materials Participating in pre-sales work and client work as necessary
◆ Discovering and verifying opportunities for new business 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

Skills

Must

Required:
◆ Strong modelling skills - neural networks, multivariate analysis (MVA), time series, regression and nonlinear models, support vector machines, and similar
◆ 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
◆ Excellentanalyticalskills
◆ Strong communication and presentation skills, both verbal and written. The successful candidates will be expected to communicate effectively with both business and technical teams

Desired:
◆ 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
Required:
◆ Post-graduate degreein Mathematics,Statistics,Engineering, Computer Science, Computational Statistics, Physics, Operations Research or other similar quantitative field
◆ Atleast three years of experience in datascience,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

Desired:
◆ Experience in the analysis of large,complex,multi- dimensional data-sets with a variety of analytical methods
◆ Experience in projects involving cross-functional teams

Nice to have

-

Languages

  • English: Upper-intermediate

Relocation package

If needed, we can help you with relocation process. Click here for more details:

WHERE
Kiev
Work Type
Data Science
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