Senior Data Scientist: Deep Learning

Added: 28/04/2020

REF: 3030

Contract: Permanent

Location: Bridgewater, Massachusetts, United States

Data Scientist (Deep Learning) 
Boston, MA

We are looking for a Sr. Data Scientist with a strong background in deep learning and familiarity with some of its applications including modeling and analysis of unstructured text and documents, images and bioimages, time-series, single-cell sequences, and clinical data in our AI and Deep Analytics group. The candidate will directly report to the Global Head of AI and Deep Analytics.


The responsibilities of the senior data scientist in AI and Deep Analytics will include:      

  • Applying AI/ML for modeling and embedding of data plus performing tasks such as classification, clustering, prediction, generation, relationship discovery, and causal inference.    
  • Close interactions with data engineers, subject matter experts (SMEs), and business stakeholders  
  • Update and report relevant results to interdisciplinary project teams and stakeholders
  • Maintain a keen awareness of recent developments in data science and cloud computing infrastructures and state-of-the-art of AI/ML/DL algorithms and research results
  • Active engagement in evaluation and coordination of both academic and startup collaborations


Qualifications & Requirements:

  • A PhD or MS degree in Data Science, Computer Science, Engineering Sciences, Applied Mathematics, and Physics with an emphasis on machine learning and deep learning
  • PhD with 3-5 years of industry experience with a strong record of accomplishments and project experience in applications of AI/ML  OR MS Degree with 10 years + industry experience with a strong record of accomplishments and project experience in applications of AI/ML.  
  • Strong familiarity with Deep Learning, neural network architectures including CNNs, RNNs, Embeddings, Transfer Learning, Attention-based Networks, and Reinforcement Learning.
  • Familiarity with Data Visualization tools/libraries and dimensionality reduction algorithms
  • Proficient in Python, SQL, and NoSQL databases
  • Familiarity with some of deep learning libraries such as Keras, TensorFlow, PyTorch, Gensim, SpaCy, OpenCV
  • The ability to work with APIs and multi-GPU machines on the cloud
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