Applied Science Manager, Applied AI

2 months ago


San Jose, United States TikTok Full time

About the team

The Applied AI (AAI) Team is a Data Science team that is part of the Monetization Integrity team in the Global Business Solutions of TikTok. It supports the Data Cycling Center, which focuses on empowering businesses with affordable and trusted data & models. About The RoleWe are looking for a Data Science Manager with a 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 the business, and providing technical leadership in end-to-end ML practice to ensure SOTA and scalable ML deliverables. Responsibilities:- Build and lead the data science team, and establish the DS/ML practice in the team.- Design a 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 junior/senior data scientists; provide career development to other team members.

Minimum Qualifications:- PhD, ., or Bachelors degree in Statistics, Economics, Computer Science or another quantitative field with -5 years of industry experience in the Data Science field-5 years in Data Science leadership and managing a team- Demonstrated excellence in a relevant AI/ML discipline (CV, NLP, ASR, , including experience with ML frameworks such as Tensorflow, PyTorch- Solid knowledge of traditional machine learning algorithms, . regression, classification, unsupervised, AB testing, hypothesis testing, and optimization- Experience in managing end-to-end data science products - data pipeline, model development, model testing and deployment, business integration Preferred Qualifications:- 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.

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