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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