Senior Data Scientist - Payment

1 Month ago • 3 Years + • Data Analyst • Undisclosed

About the job

Job Description

GoPay seeks a Senior Data Scientist to build data science solutions enhancing customer engagement and transaction growth. Collaborating with engineers, product managers, and business analysts, you'll rapidly prototype solutions, analyze large datasets, and generate actionable insights. Responsibilities include owning end-to-end solutioning, from problem definition to deployment. Experience with recommender systems, ranking, multi-armed bandits, search, and discovery is a plus. The role involves working in a fast-paced, cross-functional team leveraging robust data infrastructure to address challenging business problems in the payments industry.
Must have:
  • 3+ years relevant experience
  • Strong quantitative & problem-solving skills
  • Solid understanding of Statistics/ML fundamentals
  • Proficiency in Python or R
  • Excellent communication skills
  • Ability to write clear technical documentation
Good to have:
  • Experience in recommender systems
  • Experience in ranking, multi-armed bandits
  • Experience in search and discovery
We are looking for a data scientist to join our Data Science team at GoPay - you will create models which help grow the customer base and transactions in GoPay. You will work closely with the business, product and engineering stakeholders to identify and solve some of the most challenging business problems in the payments space. You will have the opportunity to work in a fast-paced environment in a highly cross-functional team and leverage our robust data infrastructure

What You Will Do

    • Work as part of a cross-functional team of engineers, product managers and business analysts to build data science solutions that build customer engagement and help grow GoPay’s customer base and transactions
    • Rapidly prototype data science solutions and be involved in product and feature discussions
    • Analyze large volume data and generate insights which will be actionable
    • Own end-to-end solutioning, from formulating the technical problem to deployment (along with engineers) of the solution

What You Will Need

    • At least 3 years of relevant experience
    • Strong quantitative and problem-solving skills
    • Solid understanding of Statistics/ML fundamentals and demonstrated experience in Python, R
    • Communication skills to engage with business stakeholders to understand their needs and effectively communicate the results of the analytical solutions
    • Ability to write clear and concise technical documentation
    • Experience in recommender system, ranking, multi-armed bandits, search and discovery is a plus
GoPay Data Science team builds critical ML components/models which go into the engineering systems which make GoPay a safe, trusted and fun way to do payments. Our team members come from varied backgrounds, and bring with them a wide set of skills (mathematics, statistics, machine learning, deep learning etc) which we use on some of the toughest business problems in GoPay. We are enthusiastic about both data science techniques and methods, as well as the business impact of our models, and have numerous internal forums where sharing, discussions and presentations by the team members happen.
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About The Company

GoTo is the largest technology group in Indonesia, combining on-demand and financial services through the Gojek and GoTo Financial brands. It is the first platform in Southeast Asia to host these two essential use cases in one ecosystem, capturing a majority of Indonesian consumer household expenditure.


GoTo’s mission is to “Empower Progress” by offering an unparalleled selection of goods and services through a comprehensive merchant and partner network and promoting financial inclusion through its leading payments and financial services business.

Jakarta, Jakarta, Indonesia (On-Site)

Jakarta, Jakarta, Indonesia (On-Site)

Bengaluru, Karnataka, India (Hybrid)

Surabaya, East Java, Indonesia (On-Site)

Surabaya, East Java, Indonesia (On-Site)

Bengaluru, Karnataka, India (Hybrid)

Jakarta, Jakarta, Indonesia (On-Site)

Bengaluru, Karnataka, India (On-Site)

Jakarta, Jakarta, Indonesia (On-Site)

Bengaluru, Karnataka, India (Hybrid)

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