Job
Description
You will be responsible for applying Natural Language Processing (NLP) AI techniques, performing machine learning tasks, and developing high-quality prediction systems to classify data. You will also be tasked with presenting information using data visualization techniques and handling data collection, preprocessing, and harmonization. Your key responsibilities will include: - Developing applications in machine learning and artificial intelligence - Selecting features, building, and optimizing classifiers using machine learning techniques - Understanding business objectives and developing models to achieve them, including defining metrics to track progress - Managing available resources like hardware, data, and personnel to meet deadlines - Analyzing ML algorithms for solving problems and ranking them by success probability - Exploring and visualizing data to gain insights, identifying differences in data distribution that may impact model performance - Ensuring data quality through data cleaning and supervising data acquisition if necessary - Finding and using available datasets for training - Defining validation strategies, pre-processing, feature engineering, and data augmentation pipelines - Training models, tuning hyperparameters, analyzing model errors, and designing strategies to address them - Deploying models to production As a desired candidate, you should possess: - Strong understanding of machine learning (ML) and deep learning (DL) algorithms - Architecture-level understanding of CNN and RNN algorithms - Experience with NLP data models and libraries, as well as entity extraction using NLP - Hands-on experience with TensorFlow, scikit-learn, spaCy libraries, etc. - Knowledge of transfer learning and proficient scripting and programming skills in Python and Streamlight - Familiarity with common data science toolkits such as Python, NumPy, Transformers, Fast.AI, etc. - Excellent grasp of machine learning techniques like k-NN, Naive Bayes, SVM, Decision Forests, etc. - Proficiency in query languages and applied statistics skills - Data-oriented personality with skills in Data Wrangling and Data Exploration - Experience with Tableau and DataPrep is a plus Please note that preference will be given to immediate joiners, and the salary is negotiable for the right candidate. You will be responsible for applying Natural Language Processing (NLP) AI techniques, performing machine learning tasks, and developing high-quality prediction systems to classify data. You will also be tasked with presenting information using data visualization techniques and handling data collection, preprocessing, and harmonization. Your key responsibilities will include: - Developing applications in machine learning and artificial intelligence - Selecting features, building, and optimizing classifiers using machine learning techniques - Understanding business objectives and developing models to achieve them, including defining metrics to track progress - Managing available resources like hardware, data, and personnel to meet deadlines - Analyzing ML algorithms for solving problems and ranking them by success probability - Exploring and visualizing data to gain insights, identifying differences in data distribution that may impact model performance - Ensuring data quality through data cleaning and supervising data acquisition if necessary - Finding and using available datasets for training - Defining validation strategies, pre-processing, feature engineering, and data augmentation pipelines - Training models, tuning hyperparameters, analyzing model errors, and designing strategies to address them - Deploying models to production As a desired candidate, you should possess: - Strong understanding of machine learning (ML) and deep learning (DL) algorithms - Architecture-level understanding of CNN and RNN algorithms - Experience with NLP data models and libraries, as well as entity extraction using NLP - Hands-on experience with TensorFlow, scikit-learn, spaCy libraries, etc. - Knowledge of transfer learning and proficient scripting and programming skills in Python and Streamlight - Familiarity with common data science toolkits such as Python, NumPy, Transformers, Fast.AI, etc. - Excellent grasp of machine learning techniques like k-NN, Naive Bayes, SVM, Decision Forests, etc. - Proficiency in query languages and applied statistics skills - Data-oriented personality with skills in Data Wrangling and Data Exploration - Experience with Tableau and DataPrep is a plus Please note that preference will be given to immediate joiners, and the salary is negotiable for the right candidate.
