Senior Data scientist

As a Machine Learning Engineer, you will play a key role in developing and deploying advanced models to tackle complex business challenges. Your responsibilities will include: - Developing and deploying machine learning and deep learning models to address intricate business problems. - Working with large structured and unstructured datasets to derive meaningful insights. - Designing and implementing NLP models for tasks like text analytics, classification, and information extraction. - Creating scalable data pipelines and ML workflows utilizing cloud technologies. - Utilizing GCP services for modeling, deployment, and data processing. - Implementing model training, evaluation, and optimization using TensorFlow and PyTorch frameworks. - Collaborating with diverse teams including data engineers, analysts, and product teams. - Performing feature engineering, data preprocessing, and statistical analysis. - Ensuring model performance, monitoring, and continuous enhancement in production environments. Qualifications required for this role: - Strong proficiency in Python for data science and machine learning. - Hands-on experience with Machine Learning and Deep Learning algorithms. - Expertise in Natural Language Processing (NLP). - Familiarity with ML frameworks such as TensorFlow and PyTorch. - Previous involvement in Google Cloud Platform (GCP) projects. - Solid understanding of data analysis, statistics, and predictive modeling. - Experience with SQL and data processing frameworks. Additionally, it would be beneficial to have: - Familiarity with BigQuery, Vertex AI, Cloud Storage, or Dataflow on Google Cloud Platform. - Exposure to Spark / PySpark or other big data technologies. - Knowledge of MLOps, model deployment, and CI/CD pipelines. - Understanding of LLMs or Generative AI is considered a plus. As a Machine Learning Engineer, you will play a key role in developing and deploying advanced models to tackle complex business challenges. Your responsibilities will include: - Developing and deploying machine learning and deep learning models to address intricate business problems. - Working with large structured and unstructured datasets to derive meaningful insights. - Designing and implementing NLP models for tasks like text analytics, classification, and information extraction. - Creating scalable data pipelines and ML workflows utilizing cloud technologies. - Utilizing GCP services for modeling, deployment, and data processing. - Implementing model training, evaluation, and optimization using TensorFlow and PyTorch frameworks. - Collaborating with diverse teams including data engineers, analysts, and product teams. - Performing feature engineering, data preprocessing, and statistical analysis. - Ensuring model performance, monitoring, and continuous enhancement in production environments. Qualifications required for this role: - Strong proficiency in Python for data science and machine learning. - Hands-on experience with Machine Learning and Deep Learning algorithms. - Expertise in Natural Language Processing (NLP). - Familiarity with ML frameworks such as TensorFlow and PyTorch. - Previous involvement in Google Cloud Platform (GCP) projects. - Solid understanding of data analysis, statistics, and predictive modeling. - Experience with SQL and data processing frameworks. Additionally, it would be beneficial to have: - Familiarity with BigQuery, Vertex AI, Cloud Storage, or Dataflow on Google Cloud Platform. - Exposure to Spark / PySpark or other big data technologies. - Knowledge of MLOps, model deployment, and CI/CD pipelines. - Understanding of LLMs or Generative AI is considered a plus.