Huquo Consulting Pvt. Ltd | Jobs | Data Scientist – Deep Learning Solutions | BigDataKB.com | 01-02-22

05/04/2022

Job Location: Noida

Mandatory Skills :

– Hands-on experience and proven success in building Deep Learning-based solutions (Dense & Convolutional NNs, RNNsLSTMs, Transformer-based models, etc.) and solid Python coding experience in the context of Machine Learning (primarily Python >3.6, familiarity with popular MLData Science libraries, e.g. NumPy, Pandas, scikit-learn)

– Proficiency in training large scale models in, at least, one of the following frameworks : TensorFlow, Keras, PyTorch

– Excellent knowledge of natural language processing (NLP) techniques in atleast one of the the following areas : Machine Translation, Question Answering, InformationRelation Extraction, NER, Sentiment Analysis, Feature modelling, etc.

– Knowledge of the latest SOTA research papers (NLP domain covering the following is a plus : Transformer, BERT, Google Reformer, etc.) with good understanding of algorithms and complexities that could translate into an efficient code

– Demonstrated ability to execute across the entire data pipeline

– Excellent knowledge of professional software engineering practices and best practices for the full software development life cycle

Key Requirement for the Position :

– Ability and willingness to self-learn, adapt, and guide other data science team members in new and emerging state-of-the-art technologies e.g. neural networks,

– Strong verbal and written communication skills and the ability to communicate effectively across product, development, and management teams.

– Knowledge of machine learning techniques and data engineering pipelines

– Experienced Data Scientist who possesses a passion for designing and driving data science projects forward.

– B. Tech or MTech. M.S. in Computer Science, Electronics, Data Science, Mathematics, or other related disciplines from top tier engineering institute.

Job Responsibilities :

– Utilizing Natural Language Processing tools and libraries to extract valuable business data from documents

– Applying Machine Learning Deep Learning techniques to analyse the extracted data

– Adjustment of the models and algorithms to improve the accuracy of the result

– Sharing technical expertise with the team bringing new practices and techniques

– Integration of the developed application with producers and consumers of data

– Break down large or complex data science projects into meaningful subprojects.

– Ensure a common understanding and agreement on data science project scope and goals and on any subsequent changes.

– Drive consensus on technical decisions to satisfy data science requirements.

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