Lead Data Scientist

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.

About the Role

We are looking for the data science manager with strong focus in AI/ML. You will be accountable for driving the innovation and execution of the data science practice. This includes project collaboration with business, providing technical leadership in end-to-end ML practice to ensure SOTA and scalable ML deliverables.

What You'll Do

• Build and lead the data science team, and establish the DS/ML practice in the team;
• Design strategic roadmap for long-term data science development, have knowledge of the latest industry technologies and align them with department strategies;
• Collaborate with business leaders to identify potential areas of data science applications;
• Oversee all data science projects, provide technical leadership in ideation and execution, identify potential business risks and align on the deliverables;
• Recruit, onboard and mentor other data scientists; provide career development to other team members.

Qualifications

• Bachelor degree or above in the field of Statistics, Economics, Computer Science or another quantitative field with industry experience in data science field;
• Demonstrated excellence in a relevant AI/ML discipline (CV, NLP, ASR, etc.), including experience with ML frameworks such as Tensorflow, PyTorch;
• Solid knowledge of traditional machine learning algorithms, e.g. regression, classification, unsupervised, AB testing, hypothesis testing, and optimization;
• Experience in managing end-to-end data science product - data pipeline, model development, model testing and deployment, business integration;
• Previous experience in managing data science teams.

Preferred

• Experience in managing the engineering scope, implementation of ML SDLC practice;
• Strong communication skills, for example demonstrated through documentation and presentations. Able to present findings to senior management to inform business decisions.