Liberty IT

Senior Data Scientist

Job description

Job Details

Job Title

Senior Data Scientist

Reference Number

SDSML0122

Location

Belfast UK; Dublin Ireland or remote from UK or Ireland

Contract Type

Full-Time Permanent

Closing Date

31/1/2022

Liberty IT employs over 500 people who develop a wide range of specialist and enterprise scale applications and provide technical support across the global enterprise for our parent company, Liberty Mutual. Across our two offices in Belfast and Dublin our teams live and breathe innovation, creativity and commitment to excellence - designing and implementing innovative solutions using both existing and emerging technologies. Combine that with our commitment to providing a great place to work for employees and you have the perfect place to start or grow your career.

Senior Data Scientist

As a Senior Data Scientist you will work as a lead in a collaborative to rapidly and effectively deliver great solutions that adds real value to our customers. You will be challenged. You will have the chance to be creative and have your voice heard. We will offer you a competitive salary, enable you to balance your work and life, and support you through mentoring, coaching and training programs.

In this role, you will:

  • Take a customer-centric approach to deliver real value and solve complex business problems working as a lead in a team.
  • Have a strong understanding of how the tools and analytical models you work on can contribute to the success of the project.
  • Work with customers to analyze their business problems, drive out requirements and deliver predictive modelling and meaningful recommendations that meet a real business need.
  • Work as a technical lead to apply sophisticated statistical techniques to very large data sets in the course of predictive modelling and various analytical projects.
  • Have input across all data preparation steps, including extraction, integration and the creation of derived variables to ensure the application of business rules checks and implement quality control checks.
  • Coach, mentor and provide feedback to the team.
  • Lead and support team in implementing continuous improvement opportunities across all aspects of the team.
  • Continuously develop your skills and knowledge.
  • Actively seek opportunities for you and your team to collaborate with and learn from our technical people across our organization through internal networks, events and communities of practice.

The ideal candidate will:

  • Be just as good at working with people as technology. Someone who makes a team better by being part of it, and has experience of positively leading and mentoring others.
  • Build great customer relationships by listening and empathizing with our customers to provide them with the solutions they really need.
  • Have a deep understanding of the importance and principles of writing clean, quality, high performing and secure code and champion it within their team and the department.
  • Be proactive about continuous improvement and innovation, and encourage your team to do the same. Someone who doesn’t just dream it but gets it done.
  • Share their own experiences and expertise using the right method of communication and the right level for the audience.
  • Be interested in technology and actively look for ways to increase their technical knowledge.
  • Have experience in working with machine learning and big data products within AWS

Essential Criteria

  • A PhD qualification in Mathematics, Computing, Statistics or another quantitative field and 1 year of industry experience in a relevant Data Science related position; or a Masters' qualification in Mathematics, Computing, Statistics or another quantitative field 3 years of industry experinece in a relevant Data Science related position.
  • A minimum of two years’ postgraduate relevant Data Science experience in a commercial environment or completed a PhD with experience and in-depth knowledge in the following
    • Statistical techniques such as regression analysis, cluster analysis and optimization
    • Manipulating, transforming and integrating multiple data sources on SQL ETL tools
    • Various analytical methodologies – Random Forest, Neural Network, K-means clustering or similar
    • Big Data concepts, strategies, methodologies and tools – MongoDB, Spark, Hadoop
  • Proven technical ability in working with statistical software packages including Python; R; SAS; SPSS
  • Experience in designing, building and deploying complex machine learning models (eg. non-linear regression models) that drive revenue growth or savings.

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