Senior Data Scientist

Role Description

We are seeking an accomplished Senior Data Scientist to design, develop, deploy, and optimize enterprise-grade data science and machine learning solutions that support strategic business initiatives across multiple domains. In this role, you will be responsible for the complete data science lifecycle, from translating business problems into analytical solutions and developing predictive models to deploying machine learning pipelines, monitoring model performance, and supporting data-driven decision-making throughout the operational lifecycle.

• Design, build, and continuously refine scalable machine learning models, predictive analytics solutions, and statistical algorithms using Python, R, SQL, and modern machine learning frameworks.
• Author clean, well-documented, and production-ready analytical code that follows established software engineering best practices.
• Develop data processing pipelines for structured, semi-structured, and unstructured data using Python, SQL, Spark, or equivalent technologies.
• Design and implement predictive models, recommendation systems, forecasting solutions, classification algorithms, clustering models, NLP, and anomaly detection systems.
• Actively participate in data architecture discussions, model design reviews, and technical strategy sessions.
• Continuously evaluate and optimize model performance, feature selection, hyperparameter tuning, and data quality.
• Implement and maintain robust model lifecycle management practices.
• Develop comprehensive validation frameworks including unit testing for data pipelines and model validation.
• Contribute meaningfully to MLOps pipeline design and deployment automation.
• Proactively identify data quality issues, model drift, and opportunities for optimization.
• Collaborate effectively within Agile/Scrum delivery teams.
• Maintain comprehensive technical documentation.

Qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a closely related quantitative discipline.
• Five or more years of professional experience developing production-grade machine learning models and enterprise data science applications.
• Strong understanding of statistics, probability, machine learning algorithms, and end-to-end machine learning lifecycle principles.
• Advanced working knowledge of Python, R, SQL, Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, and modern data science libraries.
• Hands-on experience designing, training, validating, deploying, and monitoring machine learning models.
• Proven experience working with relational and NoSQL databases and large-scale datasets.
• Strong SQL skills and experience performing data exploration, feature engineering, and ETL development.
• Solid experience with Git-based version control workflows and CI/CD processes.
• Hands-on experience deploying machine learning solutions on at least one major cloud platform (AWS, Azure, or GCP).
• Strong debugging, analytical thinking, problem-solving, and root-cause analysis skills.

Preferred Qualifications

• Experience designing and deploying real-time machine learning systems and large-scale AI applications.
• Familiarity with containerization and orchestration using Docker, Kubernetes, and MLflow.
• Exposure to advanced artificial intelligence concepts such as deep learning and explainable AI.
• Experience implementing automated testing, model monitoring, and MLOps best practices.

How to Apply

Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected] or contact us at View phone number on remotive.com. Learn more about Bright Vision Technologies at .