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Data Scientist

Ocbc · BANTEN, Indonesia

Weak hiring record · median 448 days open

2222

Hiring signal

Ghost risk

Open 976 days · How we score

All reasons
  • Open 976 days
  • 90% of this employer's openings are over 60 days old

In its favour

  • Still listed on the employer's own board

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Data Scientist at Ocbc. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

Data Scientist

Do you have a passion for uncovering insights from data and applying machine learning (ML) to solve problems in the dynamic world of finance?

We are seeking a highly motivated and independent Data Scientist to join our growing team!

In this role, you will

  • Play a key role in driving data-driven decision making across the financial organization.
  • Develop, implement, and maintain ML models to solve complex financial challenges.
  • Work collaboratively with stakeholders across various business units to understand their needs and translate them into actionable data solutions.
  • Clean, analyze, and interpret large datasets to identify trends and patterns.
  • Communicate complex findings in a clear and concise manner to both technical and non-technical audiences.
  • Stay up-to-date on the latest advancements in ML and financial technology (FinTech).

Qualifications

  • A strong understanding of fundamental algorithms and data structures (e.g., sorting, searching, trees, graphs).
  • Proficiency in applying basic machine learning concepts (e.g., regression, classification, clustering).
  • Experience working with programming languages like Python and R.
  • Solid foundation in statistics and probability.
  • Excellent communication and collaboration skills.
  • A passion for learning and staying informed about the latest trends in data science and finance.
  • A high degree of autonomy and the ability to manage multiple tasks simultaneously.

Bonus points if you have

  • Experience with financial data and regulations.
  • Familiarity with cloud platforms (e.g., AWS, Azure, GCP).
  • Experience developing and deploying ML models in production environments.

Skills

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