Data Scientist - Applied AI

About the team
The success of data business model hinges on the supply of a large volume of high quality labeled data that will grow exponentially as our business scales up. However, the current cost of data labeling is excessively high. The Data Solutions team is built to understand data strategically at scale for all Global Business Solution (GBS) business needs. Data Solutions Team uses quantitative and qualitative data to guide and uncover insights, turning our findings into real products to power exponential growth. Data Solutions Team responsibility includes infrastructure construction, recognition capabilities management, global labeling delivery management.

We are looking for generalists and specialists in AI/ML techniques, including computer vision (CV), natural language processing (NLP), and audio signal processing. You will be responsible for partnering with a variety of stakeholders (product, operations, policy, and engineering) and developing state-of-the-art models.

What You'll Do:
1. Design and build core capabilities by leveraging content understanding capabilities, such as natural language processing, machine learning, or computer vision, to extract insights and improve monetization strategies;
2. Develop creative solutions and build prototypes for business problems using algorithms based on the latest deep learning, machine learning, statistics, and optimization techniques;
3. Independently manage data projects from 0 to 1, and collaborate with product managers to define user stories, and success metrics to guide the development process;
4. Verify the business value and estimated revenue of the project using methods such as AB testing;
5. Collaborate with engineering teams to deploy and scale data science solutions.Minimum Qualifications:
1. Knowledge of underlying mathematical fundamentals in statistics, machine learning and analytics;
2. Experience in data modeling/analysis, with industry experience in ML/DL and one of CV/NLP/Speech;
3. Experience with exploratory data analysis, statistical analysis and hypothesis testing, and model development;
4. Fluency in SQL, Hive, Presto, or Spark and having experience working with large datasets.

Preferred Qualifications:
1. Clear understanding of data pipeline, model development, model testing and deployment;
2. Experience in CI/CD such as git and cloud services such as AWS/GCP/Azure will be highly desirable;
3. Advanced English with good communications skills; able to communicate analytical and technical content in an easy to understand way to both technical and non-technical audiences;
4. Intellectual curiosity, along with excellent problem-solving and quantitative skills, including the ability to desegregate issues, identify root causes and recommend solutions.