Data Science Specialist

ROLE & RESPONSIBILITY

• Work with stakeholders throughout the organization to understand data needs, identify issues or opportunities for leveraging company data to propose solutions for support decision making to drive business solutions.
• Adopting new technology, techniques, and methods such as machine learning or statistical techniques to produce new solutions to problems.
• Conducts advanced data analysis and create the appropriate algorithm to solve analytics problems
• Improve scalability, stability, accuracy, speed, and efficiency of existing data model
• Collaborate with internal team and partner to scale up development to production
• Maintain and fine tune existing analytic model in order to ensure model accuracy
• Support the enhancement and accuracy of predictive automation capabilities based on valuable internal and external data and on established objectives for Machine Learning competencies.
• Apply algorithms to generate accurate predictions and resolve dataset issues as they arise
• Be Project manager for Data project and manager project scope, timeline, and budget
• Manage relationships with stakeholders and coordinate work between different parties as well as providing regular update
• Control / manage / govern Level 2 support, identify, fix and configuration related problems
• Keep maintaining/up to date of data modelling and training model etc.
• Run through Data flow diagram for model development

EDUCATION

Bachelor's degree or higher in computer science, statistics, or operations research or related technical discipline

EXPERIENCE

• At least 5 years’ experience in a statistical and/or data science role optimization, data visualization, pattern recognition, cluster analysis and segmentation analysis, Expertise in advanced Analytica l techniques such as descriptive statistical modelling and algorithms, machine learning algorithms, optimization, data visualization, pattern recognition, cluster analysis and segmentation analysis
• Expertise in advanced analytical techniques such as descriptive statistical modelling and algorithms, machine learning algorithms, optimization, data visualization, pattern recognition, cluster analysis and segmentation analysis
• Experience using analytical tools and languages such as Python, R, SAS, Java, C, C++, C#, Matlab, SPSS IBM, Tableau, Qlikview, Rapid Miner, Apache , Pig, Spotfire, Micro S, SAP HANA, Oracle, or SOL-like languages
• Experience working with large data sets, simulation/optimization and distributed computing tools (e.g., Map/Reduce, Hadoop, Hive, Spark)
• Experience developing and deploying machine learning model in production environment.
• Knowledge in oil and gas business processes is preferrable.

OTHER REQUIREMENTS