Title: Graduate Software Developer Machine Learning - WS/2625

Title: Graduate Software Developer Machine Learning - WS/2625

Title: Graduate Software Developer – Machine Learning - WS/2625

Location:The Netherlands - Rijswick

Job Status:Contract – 6 months (potential for extension to 12 months)

Start Date:ASAP

Interview Date:ASAP

Open To:EU Citizen or Dutch Work Permit Holder

Job Overview: A leading global Services Company in the Oil and Gas industry seeks a Graduate Software Developer to augment their existing development team in Rijswick. You will develop prototype solutions for their oil and gas clients to help meet their exploration and production challenges. You will employ advanced analytics, machine learning, automation of business processes, real-time data collection and analysis and other techniques. Applicants are invited with a solid background in software development combined with experience in machine learning. This is a 6 month contract with the potential for an extension or permanency. The role offers an exciting opportunity to gain exposure of Machine Learning applications across the exploration and production cycle – a sector that is embracing its potential capabilities.

Supported by global offices, the Company is a leading provider of integrated software solutions, covering the entire upstream oil cycle – from finding hydrocarbons to evaluating the prospects, building the wells, and managing and optimising the production process. Their consulting services integrate expertise and processes with their advanced technologies to optimise real-time workflows and provide robust information management solutions.

The deployment of technologies across all sectors of the upstream industry has been highly evident in recent years - from greater optimisation in the field, real-time centres, predictive maintenance, cloud solutions, big data analytics, transaction based software and much more. The oil operators and service industry have embraced this new digital age and have realised dramatic efficiencies and reduced operating costs. In a world of uncertainty and the need to remain highly competitive, the drive for continued digital transformation continues to strengthen and the Company is investing heavily in machine learning applications.

The Company has been at the forefront of leading technology advancements for nearly three decades, enabling the upstream oil and gas industry to turn critical information into useful knowledge. With the advancements in machine learning, they are developing solutions for clients that help optimise workflows and add value to their decision making process. In the first instance they will develop a prototype demonstrating the key capabilities of their solution. Many of these prototypes involve the enhancement of data, building a model and demonstrating via available high-end visualisation tools.

Working closely with Technical Sales, you will quickly grasp the domain problem and develop the prototype. Specialist domain knowledge experts are available to assist. Your strength lies in your Agile approach, business learning understanding and your expertise in programming.

Responsibilities:Reporting to the European Technical Sales Manager your primary responsibilities will be to:

  • Become knowledgeable in the Company’s technology products and development tools.
  • Execute well-defined, machine learning and analytic prototypes based on the needs of client.
  • Adapt an Agile approach to prototype development.
  • Collaborate with subject matter experts, end users, services teams, and other stakeholders to develop solutions and apply the solutions using the Company’s technologies.
  • Define and take ownership of scope, deliverables, and timelines around machine learning and advanced analytic prototypes deliverables. Many are developed within 2-3 weeks.
  • Support the Services team in the architecture, design and implementation of larger-scale production deliverables.
  • Identify issues and bottlenecks that might be improved through upgrades or plugins in the Company’s technologies.
  • Keep abreast of Machine Learning applications in the market.

Working in a fast-paced collaborative environment for major oil and gas clients, this role is ideal for a highly dynamic individual with a passion for technology and an interest in advancing their knowledge/expertise of Machine Learning applications across the oil and gas industry.

Preferences: The successful candidate will have:

  • Degree in Computer Science or equivalent preferred. MSc desired.
  • Strong Agile software development expertise essential.
  • Competent software developer essential. Python and R preferred.
  • Proven Machine learning understanding essential - the development of machine learning solutions highly desired.
  • Previous experience of the upstream oil and gas industry desired but domain experts available.
  • Strong analytical problem solving skills – ability to grasp the challenges faced; the data available; and the problem to be solved.
  • Experience of data analytics highly desired. Previous experience framing and conducting analyses in a relational database environment (e.g. Oracle DB, MySQL, PostgreSQL, MSSQL) essential.
  • Experience of using PHP, and/or Ruby desired.
  • Background in statistical programming languages (e.g. R, SAS, SPS, etc.) advantageous.
  • An assertive individual with the personality and confidence to build relationships across all stakeholders of the prototype.
  • Excellent communication skills – the ability to articulate technical solutions in a coherent manner.
  • Strong project management as you may be involved in concurrent development projects.
  • Can travel as required.

Package:Based on skills and experience, a competitive Day Rate is on offer.

Other:The Company has an equal opportunity policy and is a strong supporter of gender diversity. They welcome both male and female applicants for this role.

To apply for this job:

1) Go to the Web Site Select ‘Oil and Renewable Energy Jobs” and “Review Job” and “Apply”. If not registered, please do so. Make sure you upload your CV and submit a Cover Letter.

2) Email with the job title/reference and enclose your CV and Cover Note. Our preference is for the above process as this email may take longer for review.

PS. Your Cover Letter in support of your application, should outline a) why you feel you may be particularly suited to this position (i.e. relevant skills/experience and education) b) your availability and c) your salary expectations.

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