Engineering Data Scientist

fulltime
Expired

Employment Information

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Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.

Benefits:

  • 25 days annual leave,
  • Up to 10% Bonus
  • Contributory pension scheme - Caterpillar will double the employee's contribution Up to 10%
  • Contributory share scheme - Caterpillar will match 50% of the employee's contribution.
  • Optional flexible benefits including access to health and dental care plans, EV car lease, holiday purchase.
  • Flexible working arrangements will be considered for this role, in-line with the needs of the business.
  • Sponsorship & Relocation is not supported for this role .

About IPSD

Caterpillar’s Industrial Power Systems Division (IPSD) designs, tests and manufactures 0.5 to 18L Cat® and Perkins engines that power over 5000 applications including Marine, Petroleum, Industrial Applications, Electric Generators, and Locomotives. Caterpillar’s company strategy includes sustainability as one of four focus areas and IPSD is engaged and actively preparing green energy solutions for the future.

Job Summary

The Engineering Data Systems (EDS) team is part of the engineering team at IPSD-M (Industrial Power Systems Division – Medium Engines). We are seeking an Engineering Data Scientist to join the team and grow unique skills in a rapidly developing team and specialism in the engineering domain.

Successful applicants could be a mechanical engineer with an affinity to data analytics or data analysts with an affinity for mechanical engineering.

The purpose of the EDS team is to develop and deploy engineering data analysis tools and processes to support two key customers. The first customer is the product development engineering team where the EDS team enable them to extract the maximum knowledge from vast amounts of test, and field data quickly and efficiently. The second customer is the Service and Aftermarket team where the EDS team develop digital services for end-users which enhance the performance, pro-long the product life or improve the maintenance of Caterpillar products.

The EDS team combines a unique blend of ‘big data’ data analytics with specialist mechanical engineering skill sets to deliver their tailored data services. The team actively supports future power system development and services growth across diesel, battery, hybrid and alternative fuel powertrain projects.

What You Will Do

  • Access and navigate around our data infrastructure to use data to solve product engineering & business problems.
  • Apply data science techniques on large engineering datasets (inc. timeseries data), deriving hidden insights, knowledge, and value for engineers and sharing the insights via using easy to consume visualizations.
  • Communicate analytical solutions and workflows to peers in regular reviews and presentations to customers.
  • Package analytics for production deployment as condition monitors to grow aftermarket services and end-user satisfaction.
  • Influence future data infrastructure and technologies that the department adopts, helping to drive a data driven decision making culture and improving team processes and efficiency.
  • Deploy frequently used analytics to engineering teams through secure web applications and dashboards.
  • Work with a degree of autonomy both individually, and as part of a cross-functional team to deliver complex tasks concurrently.

What You Will Have

Programming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages.

Level Working Knowledge:

  • Development of code in a specialized programming language (Python & SQL preferred) to complete a task.
  • Follows an organization's standards, policies and guidelines for structured programming specifications.
  • Develops code collaboratively with others using version control and modular coding standards.
  • Regularly peer reviews code with others to share learning and develop robust solutions.
  • Uses research techniques to identify solutions to programming problems autonomously.
  • Diagnoses and reports minor or routine programming language problems.

Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.

Level Working Knowledge:

  • Approaches a situation or problem by defining the problem or issue and determining its significance.
  • Makes a systematic comparison of two or more alternative solutions.
  • Uses logic and intuition to make inferences about the meaning of the data and arrive at conclusions.

Query and Database Access Tools: Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use.

Level Working Knowledge:

  • Defines, creates and tests simple queries by using a command language (SQL preferred).
  • Applies appropriate query tools used to connect to the data warehouse.
  • Employs tested query statements to retrieve, insert, update, clean and delete information
  • Works with advanced features and functions including sorting, filtering and making simple calculations.

Business Statistics: Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions.

Level Working Knowledge:

  • Explains the basic decision process associated with specific statistics.
  • Works with statistical functions in all aspects of job function.
  • Explains reasons for common statistical errors, misinterpretations, and misrepresentations.
  • Describes characteristics of sample size, normal distributions, and standard deviation.
  • Generates and interprets statistical data.

Engineering: Knowledge of mechanical or mechatronics engineering, internal combustion engine technology or complex control systems.

Level Working Knowledge:

  • Explains the basic operation of an internal combustion engine.
  • Describes the engineering principles that govern the performance of a physical system.
  • Works with data to optimize a system for performance, robustness, or durability.

What You Will Get

An opportunity to solve a wide variety of problems in a large engineering team and an opportunity to develop new, and grow existing, data and analytical skills in a rapidly evolving team. Many of the engineering problems the team solve are unique and require research to investigate analytical techniques which can then be applied to solve the problem.

About Caterpillar

Caterpillar Inc. is the world’s leading manufacturer of construction and mining equipment, off-highway diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. For nearly 100 years, we’ve been helping customers build a better, more sustainable world and are committed and contributing to a reduced-carbon future. Our innovative products and services, backed by our global dealer network, provide exceptional value that helps customers succeed.

NB. The panel cannot make assumptions when shortlisting therefore please demonstrate your qualifications and experience on your CV relevant to the criteria outlined.

Pending the number of applications, the criteria for the position may be enhanced to facilitate shortlisting.

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