Company: Schlumberger
Skills: Student / Recent Grad
Education: PhD/Doctorate
Location: Cambridge, United Kingdom

In order to apply for this position, applicants MUST meet the following criteria. If your resume does not match these criteria, you will not be able to apply for this position.
     


Are you looking for an internship in DATA SCIENCE?

We're the leading provider of technology and services to the energy industry across the world. At every stage of the oil and gas lifespan, we design, develop, and deliver technology that transforms how work is done.

Our technology centres across the United Kingdom are recruiting multiple Data Science Interns for 2020.
All openings listed in the following table and detailed below have flexible start dates dependent on your availability.

When applying here, make sure to include your preferred start and end dates in your CV and to name your CV file in the following format: where XXXXX is the opening reference of the internship you would like to be considered for in priority. Want to add more ? You can also upload an optional cover letter.

Location

Position

Duration

Opening Reference

Cambridge

(Cambridgeshire)

Data Science - Well Construction

6 months

C20DH

Data Science - Data Workflows

Flexible: 6 to 13 months

C20YA

Stonehouse

(Gloucestershire)

Data interpretation and Machine learning

Flexible: 3 to 13 months

S20RB

C20DH: Data Science - Well Construction - Cambridge - 3 to 13 months Flexible duration

Scope and Subject of the Opening

As a part of Well Construction drilling activities, Schlumberger records information related to:
  • The drilling tools (motor, drill bit, ...)
  • Drilling dynamics (torsional oscillations, whirl, shock and vibration, ...)
  • The drilling parameters (drilling fluids, rotation per minute, rate of penetration, ...)
  • Subsurface data (rock strength, ...)
  • Other business data (economics, personnel, maintenance...)

The goal of this internship will be to use techniques in data analytics and data science to optimize and automate the analysis of this data, in order to identify the optimum drilling tools or parameters to be used in a given scenario.

The internship will be an opportunity for the intern to learn & apply:
  • Machine Learning development in a cloud environment
  • Extracting & structuring data in cloud databases (BigQuery, SQL...)
  • The well construction domain

Responsibilities

To achieve the project goal, the candidate may need to:
  • Associate the technical drilling data with the business data by building matching rules and algorithms on a cloud environment using Google BigQuery and Dataiku.
  • Perform an outlier analysis to identify potential erroneous information in the databases
  • Build automated analysis workflows, including labeling training data and creating machine learning models to detect events in unseen data
  • Build models representative of optimum drilling conditions, perform a clustering/similarity analysis to identify the optimum drilling parameters
  • Prototype the deployment of a predictive (or prescriptive) system for modules in Schlumberger's commercial cloud software platform.

Competencies
  • Windows and Linux operating systems
  • Highly proficient in Python, and familiar with tools such as scikit-learn
  • Ability to work independently and contribute to a team
  • Good oral and written communication skills

Qualifications

Studying towards a Masters or PhD in Data Science or related field

C20YA: Data Science - Data Workflows - Cambridge - 3 to 13 months Flexible duration

Scope and Subject of the Opening

The well construction domain team looks after the integration of data generated in operations, ongoing challenges of the business and with the data analytics team continuously develop prototypes of new solutions to operational challenges and help the technology teams to expedite the delivery of new workflows to operations.

You will be involved in the development of new data-oriented workflows where guided by domain experts you will work with large sources of data in tasks like the discovery of new insights, the solution to operational questions and in helping other teams implement solution prototypes.

Your work will require basic scientific understanding of physical processes and will involve programming in python as well as the development of workflows in the company's data science platform. You will be assigned several mini-projects related to various areas of well construction, where there will be opportunity to develop new ideas and to influence the data infrastructure development of the platform.

Responsibilities
  • Perform data management tasks like merging, matching, consolidating, cleaning, etc from the different data storages available to enable the use of the data to provide actionable insights and valuable solutions
  • Work closely with Domain Champions to identify issues and use data to propose solutions for effective decision making
  • Use machine learning tools and statistical techniques to produce solutions to problems
  • Document the work that is performed so that in can be built on in the future (Manage code storage clearly and use good practices when writing code so that it can be easily understood and built on by the team)
  • Develop prototypes and proof of concepts in conjunction with the domain and data teams
  • Look for opportunities to use insights/datasets/code/models across other functions in the organisation

Competencies
  • Positive attitude and willingness to learn
  • Good communication skills
  • Python programming

Qualifications

Studying towards a Bachelors or Masters or PhD in in a field related to signal processing, engineering, applied mathematics, physics, statistics, machine learning or computer science.

S20RB: Data interpretation and Machine learning - Cambridge - 3 to 13 months Flexible duration

Scope and Subject of the Opening

You will be involved in the development of pilot project that aims at using recorded drilling data to optimize the development of new Rotary steerable system as well as the improvement of drilling trajectories. You will work with a multi-disciplinary team on the industry best steering systems to understand their behavior and provide models of these behavior to aid operations and development.

Responsibilities

Tasks will be focused on:
  • Write code to access data from different servers
  • Write scripts to process and ingest the data
  • Work with domain people to understand and develop ML models
  • Provide guidance to operations and management on learnt behaviors

Competencies
  • Python/MATLAB or other scripting language
  • Machine learning and statistics basics
  • Signal processing

Qualifications

Studying towards a Bachelors or Masters in Computer Sciences, Geosciences, Geophysics, Data Science, Signal processing or related field.

Disclaimer : Schlumberger is an equal employment opportunity employer. Qualified applicants are considered without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law.

A tradition of excellence and innovation

 

We’re the world’s leading provider of integrated pore-to-pipeline technology solutions to the oil and gas industry. We’re also a leading employer in our sector—with a reputation for hiring the best and the brightest people and keeping them at the top of their game through rewarding career-long development opportunities.

 

Each day, in 85 countries, we help our customers find and produce oil and gas in ways that demonstrate respect for both people and the environment. Today’s industry challenges call for new ideas, techniques, and solutions. If you want to drive your career and want to grow with a company that’s embraced new ways of thinking since 1927, we may have the career for you.

 

 

Schlumberger is ranked in the Global Top 10 in Rigzone's 2019 Ideal Employer Rankings.