We are looking for a leader with a passion to develop novel machine learning software systems for credit modeling and default risk prediction, deploy the systems to production, and test them to ensure all users and merchants needs are covered.
You will perform ETL to build model features using petabyte-scale datasets and develop high throughput and low latency systems to serve models in production touching the lives of more than 60 million customers every day. You will collaborate with highly innovative engineering teams to put machine learning functionalities into production systems that we build in-house.
We are looking for someone who oozes passion, ownership, and a love of building great things. The Product and Engineering teams will rely heavily on your build. You’ll have a ton of trust and responsibility. So, if challenges excite you, and you’re ready for a big one, let us know
Responsibilities
- Grow Machine Learning talent within PayPay and drive a roadmap that applies Machine Learning technologies to content discovery, engagement, recommendation, predication, risk underwriting etc.
- Work with the leadership team to identify opportunities for using ML and drive solutioning in areas of Credit
- Work with stakeholders to show them the benefits of using your system and driving adoption of the product
- Designing scalable and deployable machine learning solutions
- Define performance and validation metrics and coach the team to achieve these
- Introduce and own the process of model building and the infrastructure behind it
Requirements
- At least 3 years of experience as a manager and managing Data Engineering and Data Science Team members.
- 8+ years of software engineering experience and a proven track record of successfully architecting and taking ML systems to production.
- Designed and built multiple complex, scalable, high throughput, low latency streaming/batch processing machine learning pipelines for both data flows and algorithm execution
- Ability to explain and present analyses and machine learning concepts to a broad technical audience
- Have an extreme bias towards action. Basically, have the “Get Things Done” type of attitude.
- Be able to maintain high-performance within a high-energy and fast-paced work environment.
- You have a master degree or equivalent in Computer Science, Engineering, Mathematics or related field
- Working knowledge of PyTorch, Tensorflow or other similar frameworks is a plus
- Working experience of AWS SageMaker, Google Vertex is a plus
