- Design, develop, and deploy end-to-end predictive analytics and machine learning solutions using structured enterprise datasets.
- Build advanced forecasting models to estimate operational workloads and identify drivers of engineering complexity.
- Apply a wide range of ML techniques, including regression, classification, clustering, ensemble methods, deep learning, and time-series forecasting.
- Conduct Exploratory Data Analysis (EDA) and statistical modeling to uncover patterns, trends, and anomalies in high-dimensional datasets.
- Develop and optimize scalable ML pipelines for data ingestion, feature engineering, model training, inference, and continuous monitoring.
- Write and optimize complex SQL queries within Google BigQuery to manipulate large-scale enterprise data.
- Deploy and manage AI/ML applications on Google Cloud Platform (GCP)
utilizing Vertex AI and cloud-native services.
- Build and maintain scalable APIs and backend services using Python frameworks such as FastAPI, Flask, or Django.
- Implement MLOps best practices to ensure model reproducibility, version control, and performance monitoring in production.
- Collaborate with cross-functional teams (Engineering, Validation, Analytics) to translate complex business requirements into technical specifications.
- Develop interactive dashboards and visualization layers to communicate forecasting insights and engineering trends to stakeholders.
- Present technical insights and strategic recommendations to both technical audiences and executive leadership.
Skills
Advanced SQL, Python, Data Scientist/ AI ML, Cloud & DevOps
📌 Senior Engineer (India)
🏢 Altimetrik
📍 India
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