Data Scientist

Roles and Responsibilities

  • Independently develop algorithms and statistical models that significantly improve our current ability to make decisions based on qualitative and quantitative data.
  • Able to produce concise problem definitions and hypotheses, analyze and produce data-driven, actionable insights and present and communicate results clearly.
  • Gather and import data from different sources, write your own SQL queries, reshape, wrangle and cleanse data for quantitative analysis.
  • Measure and continue to improve the predictive accuracy of models, monitor model performance in production systems.
  • Partner with our technology teams to ensure that once proven these algorithms are implemented in robust platforms to scale for deployment across the organization.
  • Apply statistical theorems and best practices in all of our data-driven decision processes
  • Work hand-in-hand with your fellow data scientists, data engineers, operators and the product team to design and deploy data-driven solutions with high business value.


You should have

  • Exceptional CAN-DO ATTITUDE
  • Min 2yrs experience with Quantitative Analysis, Statistical Analysis and Modelling
  • Min 2yrs of applied experience in at least one statistically-oriented scripting language such as Python, R, Scala, or equivalent.
  • Solid communication skills (Bahasa Indonesia and English)
  • You are curious, analytical, fast learning and have excellent problem-solving skills
  • You must be results-oriented and willing to work in a fast and dynamic environment
  • Deep understanding of Statistical Inference and able to test and explain the assumptions and (statistical) limitations of analyses and data. Mindful and careful in interpreting results correctly.
  • Solid understanding of Linear Algebra, (Multivariate) Calculus, Applied Mathematics and Statistics, Algorithms and complex optimization
  • FSolid understanding of SQL, independently able to query databases, perform and apply joins, aggregates, filters and search patterns
  • Excellent data visualization and presentation skills
  • Bachelor’s degree in Statistics, Mathematics, Applied Math, Engineering, Computer Science, or similar advanced degree

Nice to have experience

Python data stack: Numpy, Pandas, Scipy, Scikit-learn or equivalent in R or Scala

Presentation/BI tools: Tableau, Jupyter, Kibana, Bimo, Superset, Excel, Powerpoint

A/B testing and experimentation

Experience in Deep learning, NLP, Credit Risk Scoring, Risk Analysis

Master’s or PhD Degree in Statistics, Mathematics, or Applied Maths

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Bring your passion and your A-game, and you'll fit right in