Data Scientist

Company:
Location: Bugis

*** Mention DataYoshi when applying ***

Description

Beam is Asia-Pacific’s largest and fastest-growing shared micromobility company led by technology and innovation. We’re on a mission to turn little drives into better rides and make cities flow better for everyone. Shared micromobility is one of the fastest-growing industries globally, and we are leading the way in Asia-Pacific, with fast-growing operations in Australia, New Zealand, South Korea, Taiwan and Malaysia, with many new city launches underway.

By 2030, APAC will be home to half of the world’s population and a majority of the world’s mega cities. Beam is an APAC focused micro-mobility company committed to optimising the flow of people, goods and services for the betterment of cities.


What you do:

  • Manipulate large data sets and use them to identify trends and reach meaningful conclusions to inform strategic business decisions
  • Interpret and analyse data using exploratory mathematics and statistical techniques based on the scientific method
  • Work to standardise Beam’s internal tracking dashboards, and own the process of changing central variable definitions
  • Be the central point of contact for setting up advanced analysis relating to geospatial analysis, multivariate linear regression, factor analysis/ principal component analysis, and neural networks
  • Conduct trainings to upskill current and future city operations to operate with a higher standard of analytics
  • Work with Engineering and Product teams to set up a data pipeline with the objective of make data easily accessible to operations
  • Help scale up the big data function as part of the central Strategy and Operations teams
  • Help the Product team with post-feature advanced analysis, set up A/B tests, and solve other data-related issues
  • Report to Head of Strategy and Operations

Requirements

  • SQL, Python, Redash familiarity is a must

Good to have:

  • Experience with geospatial analysis
  • Experience with Looker, Tableau platforms
  • Understanding of Unit Economics of Asset-heavy businesses

Past proven experience:

  • Degree in Statistics or other Mathematical Degree. For example: Master’s Degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields
  • Not open to fresh graduates, preferred experience in fast going startup for at least >2 years
  • Demonstrated experience applying data science methods to real-world data problems (please highlight this experience in CV)
  • Experience utilising visualisation tools to take advantage of the growing volume of available information ( please highlight this experience in CV)

Benefits

Join us to be part of the urban mobility and sustainable transportation revolution!

We are a startup in every sense of the word. Expect autonomy, visibility, breakneck pace, cutting-edge technology, barriers to overcome, problems to solve. If you are one to lead the charge, smash through barriers and create positive impact, we want to talk to you!

At Beam, we offer:

  • Opportunity to make an impact by being part of a movement that will revolutionise transportation in cities
  • Be part of an organisation in hyper-growth mode with plenty of opportunity for personal development
  • Flexible and inspiring workplace with a team of competent, motivated and fun co-workers
  • Autonomy and ownership of the work you do, with flexible hours and even unlimited days off
  • Comprehensive remuneration package and benefits

The Beam Group of Companies is an equal employment opportunity employer, dedicated to providing an inclusive, open and diverse work environment. All are welcome regardless of race, language, religion, gender, nationality, age, disability or other divisive categorisations.

By submitting an application, you acknowledge that you have read the Privacy Policy and that you consent to Beam processing data in accordance with the Privacy Policy. Please let us know if you change your mind at any time in relation to Beam processing your personal data.

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