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Data Scientist Lead

Atome

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Job Summary


Job Type
Permanent

Seniority
Lead

Years of Experience
At least 3 years

Tech Stacks
Graph
Analytics

Job Description


Here in Atome, we are looking for a data scientist lead. Atome is a BNPL (buy now, pay later) service enabler, and our data scientist team is arming it with state-of-the-art AI technologies. Our expertise in modeling and data analysis is creating endless innovation possibilities to the business.
You will be leading a team with data scientists and algorithm engineers to conquer a lot of interesting yet challenging tasks. You will be building recommender services to provide fully customized recommendations of merchants, products and contents. You will enhance the existing search engine to make it more smart in understanding the users' queries and presenting appealing results. You will also take part in some of the business modeling so that our operation and marketing strategies will be data-centric and efficient.
Reporting directly to the Head of Data Science, you will be joining a team with passion and get support from other internal functions such as business analyst and business intelligence teams. It's a journey with fast pace but also joys and excitement.

Responsibilities:
  1. Lead the data scientist team to provide fully customized user experience, including recommendations and search engine results.
  2. Conceptualize, design, prototype and implement production-quality systems. Choose the most appropriate algorithm & technical solution for each scenario.
  3. Conduct research and survey on a lot of interesting and challenging problems. Leverage state-of-the-art algorithms to boost the business growth.
  4. Implement a complete monitoring system for performance evaluation and business insights. Identify the pain points through data and understand how impact is made.

Requirements:
  1. Master's degree or PhD in Computer Science/IT/Statistics/Engineer or any other related fields.
  2. At least 3 years experience in recommender systems or search engine systems.
  3. Understand popular feature engineering & modeling techniques, such as hash embedding, graph embedding, DNN, FM, RF, XGB, etc.
  4. Strong in engineering. Understand the architectures of modeling solutions and how to ensure the quality of service.
  5. Strong in doing research & survey. Incisive in data analytics.
  6. Experienced in leading a team. With excellent communication skills, teamwork spirit and stress resistance.

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