Predictive Modeling Engineer

5 days ago


Jakarta, Jakarta, Indonesia Nikel Full time

Nikel is a leading fintech company that provides secure, efficient, and inclusive financial solutions to its customers in Indonesia. We are seeking a highly skilled Data Scientist/Senior Data Scientist to join our team and contribute to accelerating the company's innovation and data-driven strategy.

The successful candidate will have expertise in data management, predictive analytics, machine learning, and intelligent automation. They will work closely with cross-functional teams to develop innovative data solutions that enable informed decision-making and business growth.

Key Responsibilities:

  • Develop and implement advanced machine learning models for fraud predictive modeling, credit scoring, behavioral analytics, and optimization.
  • Create analytics dashboards for actionable insights and reporting, improving decision-making processes.
  • Present and explain findings to both technical and non-technical stakeholders, ensuring clarity and impact.
  • Manage end-to-end data science projects, including planning, execution, and post-implementation monitoring.
  • Continuously improve data science practices, tools, and frameworks, ensuring scalability and efficiency.
  • Collaborate closely with product and engineering teams to integrate data models into our core products.
  • Mentor junior data scientists and offer technical guidance to ensure the team's growth and success.

Required Qualifications:

  • Degree in a quantitative discipline: Mathematics, Statistics, Data Science, Computer Science, Engineering, or a related field.
  • 3+ years of experience in data analytics, data science, or related roles.
  • Solid understanding of statistical models, including their assumptions and limitations.
  • Experience in fraud detection and prevention.
  • Experience developing credit models is a plus.
  • Strong proficiency in Python, R, or SQL; experience in multiple languages is a plus.
  • Hands-on experience in the model development lifecycle as well as model operationalization (training, validation, tuning, monitoring).
  • Familiarity with data visualization tools such as Tableau, PowerBI, or Superset is an advantage.
  • Experience with cloud platforms (AWS, Azure, Google Cloud) for data processing.
  • Experience with model deployment platforms (MLFlow, SageMaker, VertexAI) is a plus.
  • Understanding of data management principles and infrastructure.


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