Data Scientist - KYC

About the Role
As a Data Scientist specializing in Computer Vision, you will be solving a variety of practical deep learning and computer vision tasks arising from different businesses in GoTo financial. You should be able to bring a new level of Deep Learning/Computer vision capabilities to the GoPay data science cloud and mobile platform.

What You Will Do

• Work with data like images, videos and real-time sensor data etc.Design, train, quantize and deploy deep learning/computer vision models
• Develop unit tests, documentation for features, evaluating, benchmarking the prediction/quality
• Communicate effectively between the business team and the engineering team to gather and implement project requirements
• Own end-to-end solutioning, from formulating the technical problem to deployment (along with engineers) of the solution
• Participate in internal and external conferences and workshops

What You Will Need

• 5+ years of experience in developing Deep Learning/Computer Vision and classic ML  models for practical applications
• Familiar with deep learning frameworks, such as TensorFlow/Keras, Caffe, PyTorch, NCNN etc. 
• Have practical knowledge of image/video processing techniques and deep learning in the computer vision domain
• World-class open data-science/deep-learning competition results and/or contributions to a deep learning/data science frameworks
• Familiarity with working knowledge in Android/iOS and GCP
• 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

About the Team 
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 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.
About Gojek
Gojek is a Super App. It is one app for ordering food, commuting, digital payments, shopping, hyper-local delivery, and a dozen other products. We are Indonesia’s first decacorn. We are  also the only Southeast Asian startup to be part of Fortune's list of 'Companies That Changed The World.'
Our Mission: To create and scale positive socio-economic impact for our customers, driver-partners, business, and MSMEs.
As of 2018, Gojek processed more than $9 billion in annualized gross transaction value across all markets where it operates - in Singapore, Vietnam, and Indonesia. We have the largest food delivery product in Asia (outside of China) and is the largest payments wallet in Southeast Asia.
Gojek contributed IDR 249 T to the Indonesian economy (equivalent to 2% of Indonesia's GDP in 2020). As of Q1 2021, the Gojek App witnessed over 190mn downloads by customers. The platform has over 2mn Driver Partners & ~900000 Merchant Partners across SEA.
About GoTo Financial
GoTo Financial brings secure, reliable, and user-friendly financial solutions to over 55 million monthly active users, more than 14 million merchants, and over 2.5 million driver-partners eager to benefit from the digital economy in the GoTo ecosystem.
GoTo Financial’s consumer services include GoPay, GoPayLater, and other financial services. We also serve businesses of all sizes through leading payment gateway Midtrans, Indonesia’s largest cloud POS network Moka and GoKasir. We also have the all-in-one merchant solution GoBiz, GoBiz Plus, GoStore, and Selly - available in Indonesia and Southeast Asia.
Gojek and GoTo Financial are committed to building a diverse and inclusive workplace and are equal opportunity employers. We do not discriminate on the basis of race, religion, national origin, gender, gender identity, sexual orientation, disability, age, education status, or any other legally protected status.