Description End user driven: Collaborate & work with end users to translate business requirements into BI / Analytics solutions Data Manipulation / processing: clean, transform, manipulate, merge and engineer data from different sources; handle all types of data (e.g.
streaming, structured, unstructured data).
Coding: contribute to internal and/or external libraries through raising issues, adding documentation and/or contributing new features; write clean, re-usable code in a language that runs in production systems.
Statistics and Machine Learning: understand and have applied a wide range of statistical or machine learning methods to build data science algorithms (e.g.
for forecasts, ranking) Carry out advanced data analytics (e.g.
correlation, reliability, confidence testing, regression, etc from source data).
Scalability, Reliability, Maintenance: proven experience in building scalable and re-usable systems and automating operations Data Domain Knowledge: understanding of data sources, and data and analytics requirements in the industry, with experience working closely with domain experts in applying data science analytics solutions All other related tasks Requirement Must have minimum bachelors degree in Computer Science, MIS/IT, Math/Statistics, Engineering or Science discipline; Minimum Six (6) years experience in designing, prototyping, deploying, and maintaining scalable data science solutions in upstream oil and gas industry; Excellent analytical, interpersonal and communication skills, and able to interact and influence others; Experienced in deriving actionable insights from data and quantifying business impact; Able to apply various data science techniques (statistical analysis, machine learning, and pattern recognition and data visualization) along with domain knowledge and subject-specific models to solve scientific, engineering & operational problems; Skilled in one or more object-oriented programming languages (e.g.
Python, R, or others); Excel, Power BI and basic web programming (CSS & HTML); Skilled in data manipulation / processing: clean, transform, manipulate, merge and engineer data from different sources; handle all types of data (e.g.
streaming, structured, unstructured data); Familiarity with database and application programming interface, including WITS/WITSML data structures & protocol; Familiarity and experienced in SQL; Good understanding of software engineering processes including version control (using Git), testing and release cycles; Knowledge and understanding of modern development methodologies: Agile using Scrum and/or Kanban; Have excellent command of English language in both speaking and writing; Experience in OSDU will be an added advantage; Proficient at using Power Query and writing expressions in Power BI