Data Science Engineer

As a Machine Learning / Data Science Engineer with 3 years of experience, you will be responsible for leveraging your expertise in Artificial Intelligence, Machine Learning, and Deep Learning technologies to design, develop, deploy, and optimize scalable ML solutions. Your role will involve collaborating closely with business stakeholders to derive actionable insights from data and solve complex business problems through data-driven approaches. You should have a strong passion for writing clean, production-grade Python code. Key Responsibilities: - Develop clean, scalable, maintainable, and well-documented production-level Python code. - Build and deploy Machine Learning and Deep Learning models for real-world business use cases. - Analyze large datasets to uncover insights, trends, and opportunities. - Design and implement statistical models, predictive analytics, and data mining solutions. - Collaborate with cross-functional teams to understand business requirements and convert them into analytical solutions. - Develop scalable and reliable AI/ML pipelines and infrastructure. - Optimize model performance and ensure efficient deployment in cloud environments. - Work on REST/FastAPI-based microservices for ML applications. - Continuously improve model accuracy, scalability, and performance. Qualification Required: - Bachelor's degree in Computer Science, Engineering, or a related field (B.E./B.Tech preferred). - 3 years of relevant industry experience in Machine Learning and/or Data Science. - Strong analytical and problem-solving abilities with a passion for working with data. - Relevant certifications in Data Science, Machine Learning, AWS, or Deep Learning are preferred. In addition, you should have hands-on experience in Artificial Intelligence, Machine Learning, Deep Learning, and strong programming expertise in Python. Familiarity with cloud platforms, preferably AWS, and experience in developing, training, testing, and deploying Deep Learning models in cloud environments are desirable. Your proficiency in Machine Learning algorithms such as Linear Regression, Logistic Regression, K-Means Clustering, and Predictive Modeling Techniques will be crucial for this role. As a Machine Learning / Data Science Engineer with 3 years of experience, you will be responsible for leveraging your expertise in Artificial Intelligence, Machine Learning, and Deep Learning technologies to design, develop, deploy, and optimize scalable ML solutions. Your role will involve collaborating closely with business stakeholders to derive actionable insights from data and solve complex business problems through data-driven approaches. You should have a strong passion for writing clean, production-grade Python code. Key Responsibilities: - Develop clean, scalable, maintainable, and well-documented production-level Python code. - Build and deploy Machine Learning and Deep Learning models for real-world business use cases. - Analyze large datasets to uncover insights, trends, and opportunities. - Design and implement statistical models, predictive analytics, and data mining solutions. - Collaborate with cross-functional teams to understand business requirements and convert them into analytical solutions. - Develop scalable and reliable AI/ML pipelines and infrastructure. - Optimize model performance and ensure efficient deployment in cloud environments. - Work on REST/FastAPI-based microservices for ML applications. - Continuously improve model accuracy, scalability, and performance. Qualification Required: - Bachelor's degree in Computer Science, Engineering, or a related field (B.E./B.Tech preferred). - 3 years of relevant industry experience in Machine Learning and/or Data Science. - Strong analytical and problem-solving abilities with a passion for working with data. - Relevant certifications in Data Science, Machine Learning, AWS, or Deep Learning are preferred. In addition, you should have hands-on experience in Artificial Intelligence, Machine Learning, Deep Learning, and strong programming expertise in Python. Familiarity with cloud platforms, preferably AWS, and experience in developing, training, testing, and deploying Deep Learning models in cloud environments are desirable. Your proficiency in Machine Learning algorithms such as Linear Regression, Logistic Regression, K-Means Clustering, and Predictive Modeling Techniques will be crucial for this role.