• Lieu: Scotland, Aberdeen
  • Salaire: £30000 - £40000 per annum + Benefits
  • Technologie: AWS Jobs
  • Type de contrat: Permanent
  • Date de publication: 13th Aug, 2019
  • Référence: JFIDATAANAL29_1565711486
Job title: Data Analyst

Location: Aberdeen

Salary: 40,000

Permanent/contract role: Permanent (full-time)

Travel required: Yes

Industry: Oil & Gas

Job description: Our Analytics team are recognised thought-leaders in the Oil & Gas industry, having developed our technologies over the last 3 years. As demand increase, both to optimise our core service lines and work with our external clients, we are seeking an ambitious Technical Data Analyst to join us. You will collaborate with our Analytics Lead, our Operations team and our clients to seek out smart solutions and increase efficiency. You will be initially based in Aberdeen but will be required to travel for client project work

You should be highly analytical, and a natural problem solver working with large, unstructured data volumes from a wide range of vintages.

Essential skills and experience required:

* A data analyst with 1 to 5 years' experience
* You will have excellent analytical and problem-solving skills using a range of data analysis techniques
* Hands-on analytical experience on data of varying vintages as well as large volumes
* Ability to understand the data landscape of a system
* Ability to present complex ideas to non-technical audiences
* Data Manipulation, wrangling and extraction techniques of unstructured and semi-structured data
* Data Visualisation
* Understanding of typical data formats and relational databases
* Use of/ development in AWS
* Appreciation and awareness of

* Python (Pandas, NumPy/SciPy, Scikit learn)
* Front end web development techniques
* Linux/Unix

* The ability to self-learn and proactively seek personal development

Desirable skills and experience (if applicable):

* Understanding of Oil and Gas industry especially subsurface
* Big data technologies such as Hadoop and Spark
* Natural Language Processing (NLP) and other Data Science techniques
* Machine Learning and Automation
* Oil & Gas knowledge would be advantageous