Job Location: Gurgaon/Gurugram
Mandatory Skills –
– Experience range 7 – 10 years with at least 2-year deep and hands-on experience in data science ecosystem (e.g. Python, Spark, Neural NetworksDeep Learning, NLP models, etc.)
– 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.
– Help Project Manager to create and maintain data science project schedules and milestone documentation, monitoring the progress of milestones and specific tasks against those schedules.
– Help Project Manager in identifying all groups and teams affected by a project to involve them – solicit their input on requirements and follow up through execution to confirm requirements are being met.
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