Data Scientist

Role Overview: At KnowDis, you will play a crucial role in developing innovative machine-learning solutions for clients in the e-commerce, healthcare, and finance sectors. As a data scientist, your responsibilities will include designing and implementing machine learning models, analyzing performance metrics, and staying updated on the latest advancements in the field. You will collaborate with a team of professionals dedicated to using AI expertise to make a positive impact on society. Key Responsibilities: - Develop and Implement Machine Learning Models: Design, build, and deploy machine learning models and algorithms for various applications, ensuring robustness and scalability. - Data Exploration and Preparation: Collect, clean, and preprocess large datasets, including feature engineering and transformation, to establish a strong foundation for modeling. - Model Training and Optimization: Train models using state-of-the-art techniques, optimize performance through hyperparameter tuning, and conduct thorough experimentation to achieve desired outcomes. - Analyze and Evaluate Performance: Utilize appropriate metrics to assess model accuracy, precision, recall, and other performance indicators, and iteratively enhance models based on results. - Experimentation and Research: Stay abreast of the latest machine learning and data science advancements, conducting experiments to explore new techniques for addressing business challenges. Qualifications Required: - Bachelor's/Master's/Ph.D. in Computer Science, Mathematics, Statistics, or related field. - Minimum of 1 to 2 years of experience in ML and AI roles. - Proficiency in Python and machine learning frameworks like PyTorch, TensorFlow, Scikit-learn, and others. - Strong understanding of statistical analysis, data modeling, and algorithmic techniques for various ML tasks. - Experience in Natural Language Processing (NLP) and/or Computer Vision (CV) is essential, with preferred expertise in specific areas like RNNs, transformer-based architectures, ViT, CLIP, Swin Transformers, DINO, YOLOv7/v8, VQA, image classification, object detection, and multimodal architectures. - Practical experience in building production-ready systems using deployment frameworks like FastAPI, NVIDIA Triton Inference Server, TorchServe, or TensorFlow Serving is a plus. (Note: Additional details about the company were not explicitly mentioned in the job description.) Role Overview: At KnowDis, you will play a crucial role in developing innovative machine-learning solutions for clients in the e-commerce, healthcare, and finance sectors. As a data scientist, your responsibilities will include designing and implementing machine learning models, analyzing performance metrics, and staying updated on the latest advancements in the field. You will collaborate with a team of professionals dedicated to using AI expertise to make a positive impact on society. Key Responsibilities: - Develop and Implement Machine Learning Models: Design, build, and deploy machine learning models and algorithms for various applications, ensuring robustness and scalability. - Data Exploration and Preparation: Collect, clean, and preprocess large datasets, including feature engineering and transformation, to establish a strong foundation for modeling. - Model Training and Optimization: Train models using state-of-the-art techniques, optimize performance through hyperparameter tuning, and conduct thorough experimentation to achieve desired outcomes. - Analyze and Evaluate Performance: Utilize appropriate metrics to assess model accuracy, precision, recall, and other performance indicators, and iteratively enhance models based on results. - Experimentation and Research: Stay abreast of the latest machine learning and data science advancements, conducting experiments to explore new techniques for addressing business challenges. Qualifications Required: - Bachelor's/Master's/Ph.D. in Computer Science, Mathematics, Statistics, or related field. - Minimum of 1 to 2 years of experience in ML and AI roles. - Proficiency in Python and machine learning frameworks like PyTorch, TensorFlow, Scikit-learn, and others. - Strong understanding of statistical analysis, data modeling, and algorithmic techniques for various ML tasks. - Experience in Natural Language Processing (NLP) and/or Computer Vision (CV) is essential, with preferred expertise in specific areas like RNNs, transformer-based architectures, ViT, CLIP, Swin Transformers, DINO, YOLOv7/v8, VQA, image classification, object detection, and multimodal architectures. - Practical experience in building production-ready systems using deployment frameworks like FastAPI, NVIDIA Triton Inference Server, TorchServe, or TensorFlow Serving is a plus. (Note: Additional details about the company were not explicitly mentioned in the job description.)