2+ Named-entity recognition Jobs in India
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We are seeking a Data Scientist with strong expertise in data analysis, machine learning, and visualization. The ideal candidate should be proficient in Python, Pandas, and Matplotlib, with experience in building and optimizing data-driven models. Some experience in Natural Language Processing (NLP) and Named Entity Recognition (NER) models would be a plus.
Analyze and process large datasets using Python and Pandas.
Develop and optimize machine learning models for predictive analytics.
Create data visualizations using Matplotlib and Seaborn to support decision-making.
Perform data cleaning, feature engineering, and statistical analysis.
Work with structured and unstructured data to extract meaningful insights.
Implement and fine-tune NER models for specific use cases (if required).
Collaborate with cross-functional teams to drive data-driven solutions.
Required Skills & Qualifications:
Strong proficiency in Python and data science libraries (Pandas, NumPy, Scikit-learn, etc.).
Experience in data analysis, statistical modeling, and machine learning.
Hands-on expertise in data visualization using Matplotlib and Seaborn.
Understanding of SQL and database querying.
Familiarity with NLP techniques and NER models is a plus.
Strong problem-solving and analytical skills.
2-5 yrs of proven experience in ML, DL, and preferably NLP.
Preferred Educational Background - B.E/B.Tech, M.S./M.Tech, Ph.D.
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๐) Problem formulation and solution designing of ML/NLP applications across complex well-defined as well as open-ended healthcare problems.
2) Cutting-edge machine learning, data mining, and statistical techniques to analyse and utilise large-scale structured and unstructured clinical data.
3) End-to-end development of company proprietary AI engines - data collection, cleaning, data modelling, model training / testing, monitoring, and deployment.
4) Research and innovate novel ML algorithms and their applications suited to the problem at hand.
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๐) Deeper understanding of business objectives and ability to formulate the problem as a Data Science problem.
๐) Solid expertise in knowledge graphs, graph neural nets, clustering, classification.
๐) Strong understanding of data normalization techniques, SVM, Random forest, data visualization techniques.
๐) Expertise in RNN, LSTM, and other neural network architectures.
๐) DL frameworks: Tensorflow, Pytorch, Keras
๐) High proficiency with standard database skills (e.g., SQL, MongoDB, Graph DB), data preparation, cleaning, and wrangling/munging.
๐) Comfortable with web scraping, extracting, manipulating, and analyzing complex, high-volume, high-dimensionality data from varying sources.
๐) Experience with deploying ML models on cloud platforms like AWS or Azure.
9) Familiarity with version control with GIT, BitBucket, SVN, or similar.
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๐) We offer Competitive remuneration.
๐) We give opportunities to work on exciting and cutting-edge machine learning problems so you contribute towards transforming the healthcare industry.
๐) We offer flexibility to choose your tools, methods, and ways to collaborate.
๐) We always value and believe in new ideas and encourage creative thinking.
๐) We offer open culture where you will work closely with the founding team and have the chance to influence the product design and execution.
๐) And, of course, the thrill of being part of an early-stage startup, launching a product, and seeing it in the hands of the users.
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