Job Responsibility
Data Processing & Management:
– Design, develop, and maintain scalable data processing pipelines for handling large datasets using both on-premise and cloud platforms (e.g., AWS).
– Ensure data quality, consistency, and accuracy through rigorous validation and cleansing processes.
Data Analysis & Insights:
– Monitor and perform comprehensive data analysis to identify trends, patterns, and correlations within large datasets.
– Generate actionable insights and present findings to stakeholders through clear and concise visualizations.
Model Development:
– Develop, test, and deploy predictive models with (deep) machine learning algorithms using frameworks such as TensorFlow, PyTorch, and Scikit-learn.
– Continuously monitor and refine models to improve performance and accuracy.
Collaboration and Support:
– Work closely with data engineers, AI engineers, and software developers to understand data requirements and provide technical support.
– Facilitate effective communication and collaboration within the AI and data teams and other technical teams.
Security and Compliance:
– Ensure the security and compliance of data handling and processing by implementing best practices and adhering to regulatory requirements.
– Conduct regular audits and assessments to identify and mitigate security vulnerabilities.
Continuous Improvement:
– Identify areas for improvement in data processing, analysis, and model development workflows.
– Stay updated with the latest industry trends and technologies related to data science and AI.
Skills and Experience
Education:
– Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field. A higher degree is a plus.
Experience:
– Minimum of 3-5 years of experience in data science, machine learning, or a similar role.
– Proven experience in processing and analyzing large datasets.
– Strong background in Python programming and data manipulation libraries (e.g., Pandas, NumPy).
Skills:
– Proficiency in machine learning frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-learn).
– Strong analytical and problem-solving skills with a meticulous and data-sensitive approach.
– Excellent communication skills with the ability to convey complex data insights to non-technical stakeholders.
– Familiarity with one of cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Apache Spark, Hadoop).
– Attention to detail and a patient, methodical approach to data handling and analysis.
Preferred Qualifications:
– Experience in fraud detection, recommendation systems, and predicting customer behavior.
– Understanding of data engineering and MLOps methodologies.
– Awareness of security best practices in data environments.
– Proficiency with data visualization software (e.g., Tableau, Power BI).
Salary:
$2,000 – $3,500, depending on the candidate’s skills and experience.
Allowances:
- Onboarding allowance, meal allowance, and transportation allowance.
- Flight ticket to return home every six months.
Benefits:
- Provided with necessary equipment and office supplies to support work.
- Annual salary review and extensive promotion opportunities across all positions.
- Participation in company activities such as holiday celebrations, monthly events, running clubs, team building, year-end parties, and annual company trips.
- Bonuses for holidays and special occasions, quarterly and annual outstanding employee awards, project bonuses, and a 13th-month salary++ bonus.
- Commitment to employee competency development through professional training programs.
- Days off: 7 days off per month, flexible scheduling.