Engineer Data

Open date: 2024-05-07
Close date: 2024-05-21 17:30
Department: Operations

Oyu Tolgoi’s workforce today is more than 97 percent Mongolian, and major strategic focus for the company is to develop a skilled workforce that is continuously learning. We aim to attract the best talent, so that we can together deliver a safe and globally competitive copper business that contributes to the prosperity of Mongolia.

The opportunity

We are looking for one (1) Engineer Data in Oyu Tolgoi LLC Technical and Integrated Planning- Technology and Data Services department based at Ulaanbaatar with 5 days on and 2 days off.

The primary purpose of this role is to play a key role in designing, developing, and implementing machine learning models and systems to solve complex business problems. The ideal candidate will have a passion for innovation and a strong background in machine learning algorithms, data engineering, and DevOps.

What the role entails

  • Assist in designing and developing machine learning models and algorithms, focusing on scalability and efficiency.
  • Contribute to implement end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, and evaluation.
  • Work closely with the IT team to deploy models into production environments, ensuring reliability, scalability, and performance.
  • Collaborate with cross-functional teams to understand business requirements and implement data-driven solutions, working closely with engineers.
  • Partner with Rio Tinto Copper Tech and IST teams on advanced analytics projects, fostering collaborative efforts for innovative solutions.
  • Develop interfaces that visualize information for business users.
  • Provide training and knowledge transfer to support the deployment and continuity of the analytics products developed.
  • Travel to OT site and other OT locations as and when required.

What you will need for this role

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or related field.
  • Strong programming skills in languages such as Python, R and SQL (advanced queries, table joins, data wrangling).
  • Familiar with machine learning libraries and frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch).
  • Understanding and application of solution design and architecture design.
  • Knowledge of statistical concepts including probability, statistical significance, regression, and hypothesis testing.
  • Experience with cloud computing solutions such as AWS and/or Azure is a plus.
  • Understand data governance principles and have experience in data management.
  • Strong analytical and problem-solving skills to diagnose and logically resolve technical problems.
  • Self-motivated, self-managed and self-disciplined and able to work well in a team environment with a strong focus on performance and quality of service.
  • Strong communication with stakeholders.
  • Good verbal and written English skills.

All interested candidates should submit the following documents:

Please click HERE to go to Oyu Tolgoi LLC Online Application System or go to the OT portal, select your vacancy and click on the link in the bottom.

Please make sure to attach the following documents:

  • CV (in English and Mongolian)
  • Cover Letter (in English and Mongolian)

If you have any enquiries, please contact the following addresses:

Monnis Tower, 1st Floor
Chinggis Avenue 15, Sukhbaatar District
Ulaanbaatar - 14240, Mongolia

Tel: + (976) - 7010-3604


All potential candidates must be medically cleared.
Only shortlisted candidates will be contacted and asked to submit additional documents

For successful candidates, please be advised that information submitted and collected during the recruitment process may be used or required by other HR functions such as Training and HR Services.

Employees of the Oyu Tolgoi LLC and subcontract companies currently working at Oyu Tolgoi mine must notify their employer of their application prior to progressing to the interview stage.

Oyu Tolgoi LLC ensures fair and transparent recruitment practices where all applicants are provided with equal opportunities and the decision on recruitment is made by committee members without any involvement of mediating individuals.