Data Analytics Specialist

4 days ago

bangalore, India beBeeData Full time

About the OpportunityAs a seasoned Data Analytics Specialist, you will be responsible for creating and deploying sophisticated data-driven solutions to address complex business challenges.This role requires strong expertise in time-series analytics, anomaly detection, and statistical methods to design and implement cutting-edge analytical models using heterogeneous data sources.You will collaborate closely with cross-functional teams to translate business requirements into actionable insights, supporting forecasting, monitoring, and risk mitigation use cases.Key ResponsibilitiesDesign and develop advanced analytical models to detect anomalies, drifts, and degradations in time-series data.Develop software in iterative cycles, with continuous validation, monitoring, and performance optimization.Deploy analytical models to production environments, ensuring stability and fleet-level validation.Collaborate with engineering, operations, and business teams to ensure alignment with operational and business needs.Ensure compliance with data governance, quality, and data science standards throughout the development lifecycle.Communicate insights clearly to technical and non-technical stakeholders.Required QualificationsBachelor's degree in Data Science, Computer Science, Statistics, or a related quantitative field.3+ years of experience in machine learning, time-series analytics, or similar analytical roles.Strong Python programming skills and experience with data processing and modeling libraries.Solid understanding of statistical methods, anomaly detection, drift analysis, and data quality monitoring.Experience working with sensor data or heterogeneous data streams.Familiarity with software development best practices, version control (Git), and deployment workflows.Good knowledge of SQL and database management.Strong analytical mindset with excellent problem-solving and attention to detail.Preferred QualificationsMaster's degree in Data Science, Statistics, or a related quantitative discipline.Experience with advanced machine learning, ensemble methods, and time-series forecasting.Hands-on experience with data preprocessing, feature engineering, and integration of external or environmental data.Familiarity with cloud platforms and MLOps pipelines.Experience with deep learning frameworks (TensorFlow, PyTorch).

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