Deskripsi pekerjaan Data Scientist PT Lintas Media Danawa
Job Requirements:
- Bachelor’s degree (S1) in Mathematics, Computer Science, Informatics Engineering, or related field.
- Open for Fresh Graduates and experienced candidates.
- Proven programming/coding experience, demonstrated through:
- Academic projects, freelance work, internships, or professional experience, and/or Portfolio such as GitHub
- Basic knowledge of DevOps, including: Docker (required), Kubernetes (a plus)
- Analytical thinking skills.
Job Responsibilities:
- Collect, clean, and validate data from multiple sources (databases, APIs, flat files) to ensure data quality for analysis.
- Perform exploratory data analysis (EDA) to uncover patterns, anomalies, and early insights aligned with business needs.
- Build and maintain efficient data pipelines to support ongoing analytical processes.
- Design, develop, and evaluate machine learning and statistical models (classification, regression, clustering, forecasting, etc.) tailored to business problems.
- Conduct feature engineering and feature selection to improve model performance.
- Run experiments and A/B tests to measure the impact of new models or features in a structured, measurable way.
- Package and deploy models to production environments using Docker, ensuring consistent performance across different environments.
- Collaborate with the engineering team to integrate models into existing systems or applications.
- Monitor model performance in production and conduct periodic retraining when performance degradation is detected.
- Work closely with product managers, business analysts, and stakeholders to translate business needs into data-driven problem statements.
- Present analytical findings and recommendations clearly to both technical and non-technical audiences through data visualizations and structured reports.
- Document methodologies, code, and experiments in a structured manner (e.g., GitHub/GitLab) to ensure reproducibility and maintainability by the team.
- Stay up to date with the latest developments in data science, machine learning, and related technologies and apply them where relevant.
- Proactively identify opportunities to leverage data for improving operational efficiency, user experience, or product performance.
