Lead Data science

Responsibilities
•Develop scalable tools leveraging machine learning and deep learning models to solve real-world problems in areas such as Speech Recognition, Natural Language Processing and Time Series predictions
•Lead your own project. Suggest, collect and synthesize requirements. Create an effective roadmap towards the deployment of a production-level machine learning application.
•MS or PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science, or similar BS with 2+ years of experience in a highly quantitative position.•Experience in Deep Learning: DNN, CNN, RNN/LSTM, GAN or other auto encoder (AE).•2+ years of hands-on experience developing machine learning models.•Ability to develop and debug in Python, Java, C or C++. Proficient in git version control. R and Matlab are also relevant.•Extensive experience with machine learning APIs and computational packages (TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels).•Familiarity with basic data table operations (SQL, Hive, etc.)•Should be able to work both individually and collaboratively in teams, in order to achieve project goals.•Must be curious, hardworking and detail-oriented, and motivated by complex analytical problems.•Must have the ability to design or evaluate intrinsic and extrinsic metrics of your model’s performance which are aligned with business goals.•Must be able to effectively communicate technical concepts and results to both technical and business audiences.