Schlumberger Analytics Engineer ( CambridgeMA02139) in Cambridge, Massachusetts

Schlumberger will attend or host university recruitment events for this position in your area.

Position: Analytics Engineer

The Analytics Engineer utilizes analytic skills in order to create solutions to support data quality and analysis initiatives. Analytics engineers could hold the role of Data scientists to utilize a variety of data management analysis tools along with applied data analytics approaches to explore and predict data solutions.

The Data Scientist participates in the areas of data science, industrial analytics, data-driven prognostics, data mining, and machine learning. Data scientist researches and assesses next-generation technologies for diagnostics and prognostics of machinery and data-driven modeling and optimization of complex systems and has advanced working knowledge and experience with machine learning algorithms and population-based meta-heuristic optimization methods.


Reports to Software Project Manager or Engineering manager.


  • Generates innovative ideas, establishs new research directions, and shapes and executes on technical projects

  • Maintains state-of-the-art knowledge and contributes to technical discussions and reviews as an expert in related areas of responsibility

  • Applies theoretical knowledge to solve industrial problems

  • Applies engineering knowledge in developing data-driven algorithms for anomaly detection, failure prediction, and optimization

  • Collaborates with field and product engineers to identify key health monitoring parameters of a system

  • Processes large multivariate data sets collected from equipment operations, manufacturing tests, and diagnostic routines

  • Communicates ideas, plans, and results effectively via oral and written reports

  • Works effectively with peers, management, operations groups, and outside organizations

  • May participate in the relevant technical reviews and audits of the projects

  • May review, mentor and coach, while define and promote usage of standards, best practices and lessons learned

  • Utilize data analysis techniques to understand the messages contained in the data

  • Construct precise combinations of the data variables to minimize memory and computation power required, while still retaining data accuracy

  • Design data acquisition solutions which preserve signal fidelity using standard techniques and systems

  • Provide accurate and usable results generated by predictive analytics

  • Discern opportunities based on the implication of each outcome of the decisions presented through prescriptive analytics

  • Apply mathematical optimization to a data set

  • Utilize data visualization to show operational and business conditions

  • Show the eventual real effects of alternative conditions and courses of action through data simulation

 Use basic programming languages, understand the object oriented paradigm to deliver analytics solutions

 Clean data utilizing record matching, deduplication, and column segmentation methods

 Produce code modularity for easy reuse in prototyping, software architecture common practices, and best practices for model exchange

 Design, code, test and implement complex programs and scripts

Previous Experience and Competencies:

  • BS / MS / PhD in computer science, mathematics, applied statistics, physics, engineering or similar disciplines with demonstrated research capability with software experience or education

Competencies to be kept current:

  • Probability theory, decision theory, statistics, machine learning, reasoning and inference frameworks

  • Software development skills and familiarity with database, programming, and analysis platforms such as .NET (C#, F#), C++, Matlab, R, Python and SQL are preferable

  • An enthusiasm for science and technology

  • Ability to work within a team of scientists and engineers and strong oral and written communication skills

  • Knowledge of industry development environments and frameworks

  • Product development & build process

  • Understanding of business strategy

  • Presentation skills

  • Review and design methods

  • Software estimation

  • Software Lifecycle Management Process

  • Project management

  • Quality management

  • Process implementation and improvement

  • Community involvement

  • Mentoring (Senior Software Engineer I and above)

  • Leadership (Senior Software Engineer I and above)


  • Analytical thinker

  • Conscious of data quality

  • Strong communication skills

  • Function independently and in a team

  • Provide creative and innovative solutions

Please apply online at

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

Schlumberger is a VEVRAA Federal Contractor – priority referral Protected Veterans requested.