About the RoleWe are looking for4 skilled and motivated Data Scientiststo join our team for a6-month projectfocused on developing data-driven solutions to solve real-world business challenges. This is aproject-based opportunity, ideal for professionals who enjoy working on focused, high-impact initiatives with clear objectives and timelines.You’ll work with large-scale datasets, cutting-edge machine learning models, and advanced analytics tools in a fast-paced, collaborative environment. While the initial engagement is limited to 6 months, there may beopportunities for continued collaboration or growthbeyond the project, depending on performance and business needs.If you have a strong foundation in statistical analysis, machine learning, and a passion for turning data into actionable insights, we’d love to hear from you..Key ResponsibilitiesGather and analyze business requirements to design data-driven solutions and analytical models.Design, develop, and implement robust analytics and anomaly detection solutions using best engineering and data science practices.Build and integrate data pipelines from multiple internal and external data sources, including real-time sensor streams and environmental datasets, to support advanced analytics and forecasting.Develop and validate algorithms for detecting abnormal patterns, drifts, degradations, and other anomalies in time-series data.Conduct risk assessments, conceptual design reviews, and ensure analytical solutions align with operational and business needs.Execute software development in iterative cycles with continuous monitoring, validation, and performance optimization.Deploy analytical models to production environments, ensuring fleet-level validation and stable operation.Collaborate with cross-functional teams (engineering, operations, business) and communicate analytical insights clearly to stakeholders.Ensure compliance with data governance, quality assurance, and data science standards throughout the development lifecycle.Required QualificationsBachelor’s degree in Data Science, Computer Science, Statistics, or a related technical field.3+ years of experience in machine learning, time-series analytics, or similar analytical roles.Strong programming skills in Python, including experience with libraries for data processing, analytics, and modeling.Solid understanding of statistical methods, anomaly detection, drift analysis, and data quality monitoring.Experience working with sensor data or other heterogeneous data streams.Proficiency with software development best practices, version control (e.G., Git), and deployment workflows.Good knowledge of SQL and database management.Strong analytical and problem-solving skills with a keen attention to detail.Preferred QualificationsMaster’s degree in Data Science, Statistics, or a related quantitative field.Experience with advanced machine learning algorithms, ensemble methods, and time-series forecasting techniques.Hands-on experience with data preprocessing, feature engineering, and environmental or external data integration for predictive analytics.Familiarity with cloud-based development and MLOps pipelines for deploying and maintaining analytical solutions.Experience with deep learning frameworks (e.G., TensorFlow, PyTorch) for advanced anomaly detection or forecasting use cases.Knowledge of control systems and industrial data analysis is a plus.