Break down a business problem into smaller components and implement ML/NLP approaches to achieve the maximum accuracy.
Work with others to select the appropriate model for the data provided, resolve various shortcomings of the models such as over-fitting, high error rate, poor F1 scores etc.
Read literature and come with out of the box solutions for hard problems.
Minimum 3 to 7 years of experience.
Strong NLP skills which include Language Modelling, POS tagging, PCFG, Named Entity Recognition,Co-reference Resolution, Question Answering.
Hands on and good understanding of various classification techniques such as Clustering, Logistic
Regression, CRFs, MEMM, Neural Networks, SVMs, Decision Trees.
Hands on experience of various IR methods including Data Pre-processing, Similarity Measures , TfIdf,Ranked Retrieval, Indexing.
Knowledge of linear algebra and dimensionality reduction algorithms such as PCA, Locality Sensitive Hashing, Autoencoders.
Programming experience in Java or Python or both is a must.
Strong interpersonal and communication skills: ability to tell a clear, concise, actionable story to the folks across various levels of the company.
Nice to have skills
Knowledge of optimization techniques like LBFGS,Gradient Descend, NM method, Back propagation etc and when to use which one.
Experience of working with large amount of data using any of the following Spark, Storm, Hadoop, Mlib,Mahout.
Knowledge of Deep Learning techniques Autoencoders, Stacked RBMs, RNNs, CNNs etc and librarieslike Theano, Torch, CuDNN, deeplearning4j, Caffe etc
Working experience of R, Matlab or Octave.