Data Science Engineer

You will be joining a specialist AI-analytics services firm in the technology-consulting sector, where you will work on-site in Pune or Mumbai. Your role will involve delivering production-ready machine-learning solutions that drive enterprise decision-making. Collaborating with statisticians, engineers, and product managers, you will be responsible for transforming complex, high-volume data into actionable insights, thereby accelerating time-to-insight for clients in the service industry. Key Responsibilities: - Apply regression, classification, and forecasting models to address business challenges. - Develop and optimize PySpark pipelines on Databricks clusters. - Create GenAI and deep-learning prototypes for impactful use cases. - Handle multi-terabyte datasets in distributed environments. - Clearly communicate insights to both technical and non-technical stakeholders. Qualifications Required: - At least 3-4 years of data science experience in production environments. - Proficient in Python, PySpark, and SQL. - Hands-on experience with Azure Databricks and MLflow. - Demonstrated expertise in time-series analysis and forecasting. - Familiarity with classical machine learning, deep learning, and GenAI frameworks. - Strong communication and stakeholder-management skills. Nice to Have: - Experience in deploying models with CI/CD on Azure. - Knowledge of MLOps best practices and monitoring. - Certification in Azure Data Engineer or equivalent. (Note: The job description does not contain any additional details about the company.) You will be joining a specialist AI-analytics services firm in the technology-consulting sector, where you will work on-site in Pune or Mumbai. Your role will involve delivering production-ready machine-learning solutions that drive enterprise decision-making. Collaborating with statisticians, engineers, and product managers, you will be responsible for transforming complex, high-volume data into actionable insights, thereby accelerating time-to-insight for clients in the service industry. Key Responsibilities: - Apply regression, classification, and forecasting models to address business challenges. - Develop and optimize PySpark pipelines on Databricks clusters. - Create GenAI and deep-learning prototypes for impactful use cases. - Handle multi-terabyte datasets in distributed environments. - Clearly communicate insights to both technical and non-technical stakeholders. Qualifications Required: - At least 3-4 years of data science experience in production environments. - Proficient in Python, PySpark, and SQL. - Hands-on experience with Azure Databricks and MLflow. - Demonstrated expertise in time-series analysis and forecasting. - Familiarity with classical machine learning, deep learning, and GenAI frameworks. - Strong communication and stakeholder-management skills. Nice to Have: - Experience in deploying models with CI/CD on Azure. - Knowledge of MLOps best practices and monitoring. - Certification in Azure Data Engineer or equivalent. (Note: The job description does not contain any additional details about the company.)