Machine Learning Analyst

Machine Learning Analyst

Thermo Fisher Scientific
Shanghai China
Not Specified
Not Specified

Job Description

Job Description :
The BI data science analyst shall join a highly dynamical and contributing BI team to provide data-driven innovative solutions and address business needs using machine learning and data mining techniques. This role will drive advanced analytics and business modelling by utilizing state-of-the-art technologies and ensure the successful application of the solutions and techniques. The candidate shall offer new and non-traditional angles on how to look at the business, identify risks and outliers, and discover business growth opportunities from a data perspective. The main responsibilities of this position are as follows:
  • Collaborate with business teams to understand the requests; use advanced techniques to solve real world problems
  • Build advanced machine learning (ML) models to help business identify issues, categorize transactions, and bring the next level of automation to the daily operations
  • Train and fine tune the ML models to steadily improve the performance and accuracy
  • Build data mining models for various data analysis purposes
  • Use NLP tools and models to mine useful knowledge and structured data
  • Apply data mining techniques on our data warehouse to spot issues and seek opportunities
  • Apply reinforcement learning to solve problems in traditional industry and processes
  • Develop, implement and document the solutions and models
  • Present and explain to non-technical background stakeholders how and why the model works
  • Constant learning of state-of-the-art deep learning, neural NLP, and data mining communities progress and developments and applying these new progresses to improve our solutions
  • Provide ad-hoc analysis using a data mindset

Profile and Requirements of the Candidate
  • Master or above degree in computer science with research direction of machine learning, data mining, natural language processing, or other related fields. Exceptional undergraduates with demonstrated academic records are also welcome.
  • Solid background in machine learning and data mining
  • Sound mathematics skills and knowledge
  • Proficiency in programming languages (Python preferred)
  • Practical experience in data science packages and libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas, numpy, scipy, etc.)
  • Practical experience in data mining tools and libraries

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