Data Scientist - Precily AI
3 - 7 yrs
₹4L - ₹25L / yr
Bengaluru (Bangalore), Delhi, Gurugram, Noida
Skills
Data ScienceArtificial Intelligence (AI)
R Programming
PythonJob Description – Data Scientist
About Company Profile
Precily is a startup headquartered in Noida, IN. Precily is currently working with leading consulting & law firms, research firms & technology companies. Aura (Precily AI) is data-analysis platform for enterprises that increase the efficiency of the workforce by providing AI-based solutions.
Responsibilities & Skills Required:
The role requires deep knowledge in designing, planning, testing and deploying analytics solutions including the following:
• Natural Language Processing (NLP), Neural Networks , Text Clustering, Topic Modelling, Information Extraction, Information Retrieval, Deep learning, Machine learning, cognitive science and analytics.
• Proven experience implementing and deploying advanced AI solutions using R/Python.
• Apply machine learning algorithms, statistical data analysis, text clustering, summarization, extracting insights from multiple data points.
• Excellent understanding of Analytics concepts and methodologies including machine learning (unsupervised and supervised).
• Hand on in handling large amounts of structured and unstructured data.
• Measure, interpret, and derive learning from results of analysis that will lead to improvements document processing.
Skills Required:
• Python, R, NLP, NLG, Machine Learning, Deep Learning & Neural Networks
• Word Vectorizers
• Word Embeddings ( word2vec & GloVe )
• RNN ( CNN vs RNN )
• LSTM & GRU ( LSTM vs GRU )
• Pretrained Embeddings ( Implementation in RNN )
• Unsupervised Learning
• Supervised Learning
• Deep Neural Networks
• Framework : Keras/tensorflow
• Keras Embedding Layer output
Please reach out to us: [email protected]
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Software Engineer, MemorresFor 2 years, I had trouble finding a company with good work culture and a role that will help me grow in my career. Soon after I started using Cutshort, I had access to information about the work culture, compensation and what each company was clearly offering.
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