Job description for Data Scientist at PT Global Loket Sejahtera
Qualifications:
- Lead the end-to-end data science process, including data collection, preprocessing, exploratory data analysis, model development, deployment, and performance monitoring.
- Develop, implement, and optimize advanced statistical models and machine learning algorithms to solve complex business problems.
- Analyze large and complex datasets to identify business trends, patterns, opportunities, and potential risks.
- Design and develop predictive and prescriptive analytics models to support business forecasting, optimization, and strategic decision-making
- Translate business challenges into data science solutions and provide actionable recommendations to relevant stakeholders.
- Collaborate with cross-functional teams, including Product, Engineering, Business, and Operations, to identify opportunities for data-driven improvements.
- Establish best practices for data science methodologies, model validation, documentation, and analytical processes.
- Monitor and evaluate model performance, ensuring accuracy, scalability, reliability, and continuous improvement.
- Present complex analytical findings and technical insights to both technical and non-technical stakeholders.
- Mentor and provide technical guidance to junior data scientists or data analysts.
Job Descriptions:
- Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Information Technology, or a related field.
- Minimum 3–6 years of relevant experience in Data Science, Machine Learning, or Advanced Analytics for Middle Level; 6+ years for Senior Level.
- Strong proficiency in Python or R, including libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Advanced knowledge of SQL, database management, data manipulation, and large-scale data processing.
- Strong understanding of statistical analysis, probability, hypothesis testing, predictive modeling, and machine learning algorithms.
- Proven experience in developing, deploying, and maintaining machine learning models in production environments.
- Familiarity with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.
- Experience with data visualization tools such as Tableau, Power BI, or Looker.
- Understanding of MLOps, model monitoring, version control (Git), and machine learning deployment workflows.
- Strong analytical thinking, problem-solving, and critical-thinking skills.
- Excellent communication skills with the ability to translate technical findings into actionable business insights.
- Ability to work independently, manage multiple projects, and collaborate effectively with cross-functional teams.
