Deskripsi Pekerjaan:

[TALENT POOL ONLY]

• Work with stakeholders throughout the organization, partners and potential clients/tenants to identify business opportunities from technical perspectives.
• Perform data mining and data analytics from tenants’ databases for certain business use cases determined by the tenants or our analytics services determined solely based on the data potential.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets based on the business use cases, working with financial/banking experts.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes using regression models, machine learning or artificial intelligence.
• Engage and work together with data analytics and data provider partners from Indonesia or overseas to develop solutions for various analytics use cases, such as lead generation, cross-selling/upselling, credit risk analysis etc.
• Develop company A/B testing framework and test model quality.
• Develop processes and tools to monitor, analyze and improve model performance and data accuracy.
• Work with software engineers to develop data platform infrastructure.

Kualifikasi:

• We’re looking for someone with 3-6 years of experience manipulating data sets and building statistical models, has a Bachelor’s or Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field.
• Strong problem solving skills with an emphasis on product development.
• Good understanding of fundamental machine learning and data science.
• Ability to capture and translate business needs into a viable solution.
• Experience using programing languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.), advance statistical techniques and concepts with their real-world advantages/drawbacks.
• Ability to deploy of a variety of machine learning or advance statistical techniques to production.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• Experience with distributed data/computing tools is a plus. Such as Map/Reduce, Spark, Spark, MySQL, etc.
• Experience developing data pipeline with or as data engineer is a plus.