Qualifications:
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
- Minimum of 2 years of experience as a Data Scientist or in a relevant analytical position.
- Proficiency with statistical analysis and machine learning techniques, including supervised and unsupervised learning methods.
- Strong experience in programming languages such as Python or R for data analysis, along with libraries like Pandas, NumPy, and Scikit-Learn.
- Familiarity with data visualization / Business Intelligence tools such as Tableau, Power BI, or Matplotlib.
- Experience with SQL for database querying, along with familiarity with big data frameworks (e.g., Spark or Hadoop).
- Ability to design and deploy predictive models and machine learning algorithms for various business use cases, with experience in AI or AI tools (e.g., TensorFlow, Keras, or OpenAI models).
- Strong adaptability to work across diverse product areas within the company and to translate data insights into actionable strategies.
- Excellent communication and collaboration skills, with the ability to explain complex analytical concepts to non-technical stakeholders.
- Relevant certifications in Data Science, Machine Learning, or specific tools (e.g., Google Data Engineer, AWS Certified Machine Learning) are a plus.
- A strong portfolio showcasing relevant data science projects is an advantage.
- Willing to be placed in Bandung, West Java.
Job Description:
- Collaborate with cross-functional teams to understand business goals and design data-driven solutions tailored to company products.
- Develop and implement machine learning models to solve complex business challenges and drive insights for product development and user engagement.
- Conduct data analysis, data mining, and statistical analysis to uncover patterns, trends, and insights that inform strategic decisions.
- Create and maintain clear, actionable, and visually compelling data reports and dashboards.
- Continuously evaluate model performance and tune models to enhance accuracy and reliability over time.
- Ensure the integrity and quality of data used for analysis, managing data collection processes, data cleaning, and preprocessing.
- Communicate findings effectively to both technical and non-technical team members to guide product improvements and business strategy.
- Stay up to date with industry trends and emerging techniques in data science, machine learning, and analytics to apply best practices within the company.
