西安招聘

KEY ACCOUNTIBILITIES:
1. Provide data analysis and up-to-date research in AI technologies for real-world applications;
2. Formulate big data and AI problems, design and build pipelines to meet various business needs in a real-world setting;
3. Perform real-world (big) data analysis using machine learning and AI methods with specialization in one of the following areas:
? Data science: data cleansing, transformation and normalization, association analysis, data mining (prediction, classification), time series analysis, workflow optimization, visual analytics (business intelligence);
? AI/Machine Learning: supervised/unsupervised/reinforcement (MCTS)/transferred learning, deep learning (cNN, rNN, LSTM, GAN), AI applications in automation
? Natural Language Processing (NLP): machine translation, semantic analysis, content digest, text mining, knowledge graphs, interactive/visual NLP systems;
4. Take ownership and complete big data & AI projects with business partners, coordinate with engineers, and IT to make scalable big data and AI deployment;
5. Analyze and share cutting-edge big data and AI technologies related to businesses, promote big data & AI results and best practices across businesses

REQUIREMENTS:
1. Master/PhD in STEM or related areas (data science, AI, machine learning, operational research, biomedical engineering, biostatistics) with (preferably industrial) experience in data analysis;
2. Excellent problem analysis and solving skills with outstanding communication and teamwork capability, good sense of data and outstanding research capability;
3. Hands-on experience in real-world data analysis applications with competency of building practical data analytics pipelines with result visualization (using Python, R, Java, NoSQL, etc.), and knowledge in (deep) learning frameworks (Tensorflow, Pytorch, Spark, AutoML, RapidMiner, Weka, etc.) preferably hands-on experience;
4. Experience in visual analytics (D3, AngularJS, processing, Silverlight, etc.) and business intelligence tools (Tableau, Qlik view, Sisense, MS BI, etc.) is a plus;
5. Knowledge in operation analytics, optimization in pharmaceutical and clinical domains is preferred;
6. Familiarity with clinical informatics & analytics, drug development, biology, chemistry and/or genomics is a plus.

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