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Data Scientist

3 weeks ago


Sunnyvale California, United States SQL Pager Full time

Please apply using the following link

Responsibilities
  •  Help design, implement, and validate the ML Pipelines while collaborating with other data scientists. 
  •  Coordinate and collaborate with other Software Development group so that ML Pipeline fits well with the rest of our software applications. 
  •  Balance adding new features with the need for stability and performance. 
  •  Grow development capabilities to align with the pace of business needs. 

 
Qualifications
  •  Master's degree or higher in Computer Science, Computer Engineering, Electrical Engineering or similar discipline with industrial experience in software development 
  •  3+ years of experience with Python coding 
  •  3+ years of recent experience working as a Data Scientist in industry 
  •  Experience with developing production-grade code, preferably in Python 
  •  Experience with data science and machine learning, including Python libraries such as NumPy, SciPy, Pandas and Scikit-learn 
  •  Strong professional written and verbal communication skills 
  •  Ability to pass a Data Science skills-based test 
  •  Experience with relational or NoSQL databases such as Oracle/Cassandra/Redis or similar 
  •  Ability to create model-ready data from raw data, at scale 
  •  Ability to translate business problems into data science pipelines 
  •  Comfort with ML theory to recommend solutions beyond the standard libraries 
  •  Must be able to work independently and as part of a diverse interdisciplinary and international team 
  •  Communicates clearly to technical and non-technical audiences 
  •  Empathy with customer business challenges 
  •  Ability to map business problems to software and data science techniques. 
  •  Understanding of fundamental data science and machine learning pipeline including data cleansing, feature engineering, imputation, model tuning, and model prediction 
  •  Basic understanding of the pros and cons of different machine learning algorithms, and basic understanding for different types of open source ML frameworks 
  •  Understanding of hypervisors/containers, especially Docker