Jobs at Gramener

Details of the role

About Gramener

We help consult and deliver solutions to organizations where data is at the center of decision making. We have our product and services which help makes this easier: by analyzing and visualizing large amounts of data. We are looking out for people who can experiment, innovate and explore the edges.

Job roles and responsibilities of a Sr. Data Scientist (Deep Learning)

  • You will help our Labs team explore and create innovative solutions:
  • Understand, contribute to and evaluate funnel of opportunities for AI Labs to work on
  • Explore and advance the state-of-art in Machine learning and Deep Learning approaches to problems across broad opportunity space
  • Work independently or as part of a team to create solutions that solve difficult problems
  • Guide team of analysts to offer exceptional solutions to clients, across domains.

Work Location: Bengaluru

Skills and Qualification for Sr. Data Scientist (Deep Learning)

  • Background in Computer Science/Computer Applications or any quantitative discipline (Statistics, Mathematics, Economics/Operations Research etc.) from a reputed institute. Proficiency in Linear Algebra
  • Passion towards research and experimentation resulting in structured solutions for problems; should have published research and participated in global forums
  • 3-5 years of experience using analytical tools/languages like Python & R on large scale data; should be able to interpret and convert a research paper into code
  • Should show proficiency with variety of approaches- supervised, unsupervised, semi-supervised, reinforcement, self-learning, feature learning, anomaly detection and association
  • Should show proficiency with variety of models - Artificial neural networks, Decision trees, SVM, Regression, Bayesian analysis and Genetic algorithms
  • Strong experience in one or more of these areas of analytics – text, image, video, NLP, autonomous agents and systems, Geographic information systems.
  • Must have strong experience in popular frameworks like Open CV, PyTorch, Theano, Tensor Flow, Caffe. Experience working with pre-trained models, awareness of state-of-art in embeddings and applicability for use cases
  • Strong applied fundamentals in data management, parallel computing and distributed systems; strong experience with deploying and productionizing models on cloud and premise.

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