As our data sientist based in Jakarta, You will advocate, evangelize and build data-fuelled products that help our customers improve customer insights. You’ll dig in and become an expert on Mobile Operator datasets. You will provide insight into leading analytic practices, design and lead iterative learning and development cycles, and ultimately produce new and creative analytic solutions that will become part of our core deliverables.

RESPONSIBILITIES

You will work with cross-functional team members internally as well as those of partners to identify and prioritize actionable, high-impact insights across a variety of core business areas. You will lead applied analytics initiatives that are leveraged across the breadth of our solutions for Mobile Operators You will research, design, implement and validate cutting-edge algorithms to analyze diverse sources of data to achieve targeted outcomes. As our data scientist, you will provide expertise on mathematical concepts for the broader applied analytics team and inspire the adoption of advanced analytics and data science across the entire breadth of our organization. You will also be in a client facing role.

REQUIREMENTS

Nice to Have

  • Bachelors in a quantitative field (CS, Stats, Engineering, Physics, etc.)
  • 2+ years professional experience working in a quantitative and analytical role
  • Fluent in at least one object-oriented programming language (Python highly preferred)
  • Ability to query a SQL and/or NoSQL database efficiently
  • Proficiency in statistical model development including data cleaning, model building and model performance testing
  • Ability to interpret the data and extract business insights and action items
  • Experience with data visualization
  • Familiarity with a cloud computing platforms such as Amazon AWS or Google Cloud Platform
  • Eager to learn new languages and tools when needed
  • Great oral and written communication skills
  • Ability to work independently or on a team
  • Strong desire to work in a fast-paced start-up environment
  • Master’s degree in a quantitative field
  • Experience setting up and using big data frameworks such as Spark
  • Experience with automating and productionizing data pipelines and predictive models
  • Experience building dashboards