Position: Data Scientist Architect/Consultant
Company: GlobalLogic
Category: Data Science
Experience required: 5y
English level: intermediate

We are looking for a a Data Scientist (Associate / Consultant level) to join our ambitious project dedicated to one of the Clients of our Fin-tech portfolio.

The successful candidate will be working as a part of a Scrum team located in Poland. It's expected that he will proactively take part/ lead development and execution of advance predictive model, analytical rigor and statistical methods to analyze and visualize large amounts of data, using advance statistical modeling techniques and mathematical analyses to discover insights and identify opportunities.

A team comprised of key specialists together with onsite stakeholders from the UK is required to establish data model and framework that captures internal and external structure and unstructured data sources to enable predictive modeling and insights and design state of the art descriptive, diagnostic and predictive algorithms based on the business requirements.

It is a great chance to become a part of a distributed, cross-functional team based in Poland. This Project is a part of the Multi-Year Program Plan.

Job Description
Have 5+ years experience in working with AWS (DS/ML Stack).
Solid knowledge of PySpark.
ML Ops experience: knowledge of a variety of machine learning techniques + hands on Amazon Sagemaker.
Solid experience working with LINUX software.
Good understanding of SDLC life-cycle (Dev, test, preprod, production and the CI/CD pipeline).
Familiar with tools like Git, Bash, etc. 
Team player skills with ability to work in distributed delivery environment.
Analytical mind and business acumen.
Good English communication skills (written & spoken). 
 

Nice to have:

BSc/BA in Computer Science, Engineering or relevant field.
Certifications: SAS, OS, CISSP, II, IASAE, CAP.
AWS certification would be an asset.

Job Responsibilities

Identify valuable data sources and automate collection processes
Undertake preprocessing of structured and unstructured data
Analyze large amounts of information to discover trends and patterns
Build predictive models and machine-learning algorithms
Combine models through ensemble modeling
Present information using data visualization techniques
Propose solutions and strategies to business challenges
Collaborate with engineering and product development teams