JOB DETAILS

JOB DETAIL

Data Architecture:
• Design and implement scalable and efficient data architectures to support data integration, storage, and retrieval.
• Create and maintain data models, including conceptual, logical, and physical models, to ensure data consistency and integrity.

Data Science:
• Analyze large datasets to uncover actionable insights and trends that drive business decisions.
• Develop and deploy predictive models using machine learning algorithms and statistical techniques.
• Create data visualizations and dashboards to effectively communicate findings to stakeholders.
Collaboration:
• Work with cross-functional teams to understand business requirements and translate them into data solutions.
• Collaborate with IT and business stakeholders to integrate data solutions into existing systems and processes.

Data Management:
• Maintain and optimize data pipelines to ensure efficient data processing and transformation.
• Oversee the management of data warehouses, data lakes, and other data storage solutions to optimize performance and reliability.
• Design and implement data integration solutions to consolidate data from various sources, ensuring seamless data flow and consistency across systems.
• Troubleshoot and resolve data-related issues to ensure continuous availability and reliability.

Continuous Improvement:
• Stay updated with emerging technologies and industry trends in data science and data architecture.
• Continuously seek opportunities to enhance data processes and methodologies.

REQUIRED WORK EXPERIENCE

• Male or Female age 32 – 40 years old
• Bachelor’s degree in computer science, Data Science, Engineering, or a related field (or equivalent experience) and Master's degree is preferred for Data Scientist with GPA 2.75 up
• 8 years of work experience in data architecture or data science roles, with a strong track record of managing and analyzing large datasets.
• Technical Skills: Proficiency in data modeling and data warehousing technologies (e.g., SQL, NoSQL, ETL tools).
• Experience with data science tools and languages (e.g., Python, R, MATLAB).
• Knowledge of machine learning algorithms and statistical analysis.
• Familiarity with data visualization tools (e.g., Tableau, Power BI).
• Understanding of cloud platforms and big data technologies (e.g., AWS, Azure, Google Cloud, Hadoop, Spark).
• Good command of English TOEIC score 550
Preferred Qualifications:
• Experience with advanced analytics, artificial intelligence, or big data solutions.
• Knowledge of data privacy regulations and best practices.