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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 understand our capabilities, client scenarios across industries and recommend value driven solutions to delight our customers.
ABOUT THE SR. DATA SCIENTIST (NLP) JOB ROLE
You will help our clients solve real-world problems by tracing the data-to-insights lifecycle:
Understand business problems, making sense of the data landscape & footprint, performing a combination of exploratory, Machine Learning & Advanced Analytics
Create, experiment with and delivery innovative solutions in a consultative mindset to client stakeholders
Guide team of analysts to offer exceptional solutions to clients, across domains.
Work Location: Hyderabad/Bangalore
QUALIFICATION AND EXPERIENCE FOR THE SR. DATA SCIENTIST (NLP) ROLE
Background in Computer Science/Computer Applications or any quantitative discipline (Statistics, Mathematics, Economics/Operations Research etc.) from a reputed institute.
3-5 years of experience using analytical tools/languages like Python & R on large scale data
Must have Semantic model & NER experience
Experience working with pre-trained models, awareness of state-of-art in embeddings and applicability for use cases
Experience on Deep Learning for Image processing, Video analytics will be a plus
Must have strong experience in NLP/NLG/NLU applications using any popular Deep learning frameworks like Opencv, PyTorch, Theano, Tensor Flow, Caffe. Should have implemented solutions for industry use cases.
Demonstrated ability to engage with client stakeholders at multiple levels and provide consultative solutioning across different domains
Deep knowledge of techniques such as Linear Regression, gradient descent, Logistic Regression, Forecasting, Cluster analysis, Decision trees, Linear Optimization, Text Mining etc.
Strong applied fundamentals in data management, parallel computing and distributed systems; experience in productionizing & retraining models
Ability to guide and mentor teams of associates on solution development and approaches
Broad knowledge of fundamentals and state-of-the-art in NLP and machine learning
Coding skills in one or more programming languages such as Python, Scala, Java, C, C++
Expert / high level of understanding on language semantic concepts & data standardization
Proven track record of successful models and practical implementation
Hands-on experience with popular ML frameworks such as TensorFlow
Experience with application development practices at scale, from problem definition to deployment.
Familiarity with Cloud services such as AWS, SageMaker etc. is considered a plus
Develop and apply Statistical Modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications
Knowledge in Machine Learning techniques in entity resolution, common speech products or text search domain