广州招聘

Job Description
The data scientist will be part of the technical execution team that will support in developing the technical end products to customers. This role will include the analysis of big data from customers to derive root causes, data parameters and algorithms that will be integrated into the digital offering that is provided to end customer. You will be responsible for developing big data analytics solutions to solve complex business problems. Here, you will be required to work with large data sets using quantitative techniques and build complex statistical models that learn from big data. This role will require you to collaboratively work with other product team members in Product R&D and developing cutting edge, creative and advanced analytic solutions and processes.

Duties and Responsibilities
Develop conceptual designs or models to address requirements.
Analyze problems to determine technical solutions.
Decide what procedures will be required to solve technical problems.
Identify new and existing products, technologies, and/or architectures to solve design, development, and operational problems.
Analyze data using mathematical/statistical methods.
Apply mathematical or computational methods and lines of reasoning.
Conduct analysis of metadata.
Develop tools and techniques for analysis.
Exploit, fuse and use data and data sources.
Identify and analyze anomalous data (including metadata).
Analyze data using appropriate tool set.

Desired Skills and Experience
MSc or PhD in data mining, machine learning, statistics, math, engineering, computer science, or other quantitative discipline.
5+ years overall development experience with terabyte or larger size poly-structured data sets.
Proficient in some or all of the following machine learning techniques: Linear & Logistic Regression, Linear Discriminant Analysis, Decision Trees, Random Forests, Naive Bayes, K-Nearest Neighbors, Support Vector Machines, etc.
Have deep understanding of Neural Networks techniques: Backpropagation Network, Convolutional Neural Network, Recurrent Neural Network, Long Short-term Memory Network, etc.
On-hand experience with machine learning frameworks on time sequence data analysis, such as PyTorch, Keras, TensorFlow, Theano, Scikit-Learn, etc.
Demonstrable programming ability in different programming languages such as Python, C/C++, Java.
Experience in handling real world large datasets through project work, internships or employment

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