เงื่อนไขการค้นหา

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Data Analysis, Automation, Python

ประเภทงาน:

งานประจำ

• 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.

ทักษะ:

SQL, Python, SAS

ประเภทงาน:

งานประจำ

• Manage and plan the data direction and strategy for business need.
• Drive successful of data insight initiatives and effective collaboration with stakeholders.
• Analyze business requirements and identify business problems into an analytics question and gain a deep understanding of models and algorithms capability and limitations.
• Create reports and dashboards based on data mining, evaluation, analysis, and visualization.
• Collaborate with key stakeholders including the Executive, Business Units, Data and IT teams to identify opportunities for leveraging company data to drive business solutions.
• Coordinate with the software developers, data engineers and data scientists to oversee the delivery of analytics solutions and formulate strategy for technology adoption and impact measurement.
• 5 years of experience as a data analyst or business data analyst.
• Advanced knowledge in SQL and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience with data studio, Big Query,model,generative AI.
• Experience with R, Python, SAS, SPSS, other analytic tools.
• Experience supporting and working with cross-functional teams in a dynamic environment.