Data Scientist

As Data Scientist, you will be working with high complex structured and unstructured datasets. Yes, we are talking terabytes. You will be building Statistical, Machine Learning, and/or Deep Learning models to solve business problems, improve operation, and build data products.

Responsibilities:

• Build state-of-the-art Deep Learning models to tackle Computer Vision and NLP problems
• Work with data/product engineers to deploy it to production and/or build a data product out of your ML models
• Communicate with the stakeholders to understand the business problem, solve the problem using data, and effectively present the insights/results

Qualifications:

• B.S./M.S./PhD in mathematics, statistics, data science, computer science, electrical engineering, or related field
• Good understanding of data science: data visualization, regression, clustering and classification
• Fluent in Python (Numpy, Pandas, Scikit-Learn)
• At least 1 year experience working with Machine Learning (Decision Trees, SVMs, Logistic Regression, PCA, Kernel Methods, LDA, QDA)
• At least 1 year working with Deep Learning. Being fluent in at least one DL framework (e.g. Tensorflow, Theano, Keras, MxNet, PyTorch, CNTK)
• Alternatively opening for someone with data analytics background. 
• Experience working with big data is a plus
• Experience with parallel/distributed/cloud computing is a plus
• Experience training Deep Learning models on multiple GPUs is a plus
• Knowledge on (Deep) Reinforcement Learning is a plus
• Experience with unsupervised and generative models are a big plus (e.g. Autoencoders and GANs)
• Experience with multi-task learning is a big plus
• Proficiency in SQL and MongoDB
• Good command of English
• Can self-manage a project from start to finish
• New graduates having worked with ML/DL in the academia are welcome

Benefits:

• Group health insurance.
• Subsidized gym membership
• You pick your equipment (Mac / Windows)
• Semi Flexible working hour 
• Work from home day !! 
• Free Snacks and Drinks 
• Free lunch on Friday 
• Friday Wow Massage !!