Sr. Data Scientist

As a Machine Learning Engineer at our company, your primary focus will be on applying Natural Language Processing (NLP) AI techniques, implementing machine learning algorithms, and constructing high-quality prediction systems for data classification. You will also be responsible for presenting information using data visualization methods, as well as conducting data collection, preprocessing, and harmonization. **Roles and Responsibilities:** - Develop applications in machine learning and artificial intelligence, including selecting features, building, and optimizing classifiers using machine learning techniques. - Understand business objectives and develop models to help achieve them, along with defining metrics to track progress. - Manage available resources such as hardware, data, and personnel to meet deadlines. - Analyze ML algorithms suitable for solving a given problem and rank them based on success probability. - Explore and visualize data to gain insights, identify differences in data distribution that could impact model performance in real-world deployment. - Verify data quality and ensure it through data cleaning. - Oversee the data acquisition process if additional data is required. - Identify available datasets online for training purposes. - Define validation strategies, pre-processing, feature engineering, and data augmentation pipelines. - Train models, tune hyperparameters, analyze model errors, and design strategies to address them. - Deploy models to production. **Desired Candidate Profile:** - Sound understanding of Machine Learning (ML) and Deep Learning (DL) algorithms. - Architecture-level understanding of CNN, RNN algorithms. - Experience with NLP data models and libraries, entity extraction using NLP. - Hands-on experience with TensorFlow, scikit-learn, spaCy libraries, etc. - Proficient in transfer learning, Python programming, and Streamlit. - Familiarity with common data science toolkits like Python, NumPy, Transformers, Fast.AI, etc. - Excellent knowledge of ML techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests, etc. - Proficiency in query languages, applied statistics, data wrangling, and exploration. - Experience with Tableau and DataPrep is a plus. **Additional Company Details:** - Preference for immediate joiners, and salary is negotiable for the right candidate. If you are passionate about machine learning, AI, and data science, we encourage you to join us in Pune, Maharashtra. For more information or to apply, please reach out to us at info@redbixbite.com or HR@redbixbite.com. As a Machine Learning Engineer at our company, your primary focus will be on applying Natural Language Processing (NLP) AI techniques, implementing machine learning algorithms, and constructing high-quality prediction systems for data classification. You will also be responsible for presenting information using data visualization methods, as well as conducting data collection, preprocessing, and harmonization. **Roles and Responsibilities:** - Develop applications in machine learning and artificial intelligence, including selecting features, building, and optimizing classifiers using machine learning techniques. - Understand business objectives and develop models to help achieve them, along with defining metrics to track progress. - Manage available resources such as hardware, data, and personnel to meet deadlines. - Analyze ML algorithms suitable for solving a given problem and rank them based on success probability. - Explore and visualize data to gain insights, identify differences in data distribution that could impact model performance in real-world deployment. - Verify data quality and ensure it through data cleaning. - Oversee the data acquisition process if additional data is required. - Identify available datasets online for training purposes. - Define validation strategies, pre-processing, feature engineering, and data augmentation pipelines. - Train models, tune hyperparameters, analyze model errors, and design strategies to address them. - Deploy models to production. **Desired Candidate Profile:** - Sound understanding of Machine Learning (ML) and Deep Learning (DL) algorithms. - Architecture-level understanding of CNN, RNN algorithms. - Experience with NLP data models and libraries, entity extraction using NLP. - Hands-on experience with TensorFlow, scikit-learn, spaCy libraries, etc. - Proficient in transfer learning, Python programming, and Streamlit. - Familiarity with common data science toolkits like Python, NumPy, Transformers, Fast.AI, etc. - Excellent knowledge of ML techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests, etc. - Proficiency in query languages, applied statistics, data wrangling, and exploration. - Experience with Tableau and DataPrep is a plus. **Additional Company Details:** - Preference for immediate joiners, and salary is negotiable for the right candidate. If you are passionate about machine learning, AI, an