
Senior Data Scientist- AzureML/SageMaker
- Bangalore, Karnataka
- Permanent
- Full-time
- Data Scientist at Rockwell Automation, you'll join an analytics team of engineers, product managers, and partners that's driving the next wave of AI-powered features for our platform.
- You'll partner with process engineers and operations leads to develop predictive-maintenance models, improve throughput and yield, and lead cost savings across manufacturing lines.
- You'll own end-to-end projects—scoping data-collection architectures, prototyping machine-learning solutions for anomaly detection and quality control, deploying models into our IIoT platform, and setting up real-time monitoring dashboards. You'll also mentor junior analysts, collaborate with R&D on pilot projects (e.g. generative-AI for defect inspection), and help define our roadmap for advanced-analytics capabilities.
- If you relish solving complex, client-facing industrial problems, translating varied data sources into clear business recommendations, and progressing as a trusted analytics partner for our clients, Rockwell Automation is where you can accelerate both your career and your clients' success.
- You will report to Lead Sr Solution Architect of the function and will work from our Electronics City, Bengaluru Office in Hybrid work model.
- Lead end-to-end data-science projects: define hypotheses, design experiments, build features, train & validate models, and deploy in production.
- Partner with Engineering to integrate ML services (TensorFlow/PyTorch) into our microservices architecture, and with Marketing to A/B-test data-driven campaigns.
- Build scalable ETL pipelines (Airflow, Spark) and design data schemas (SQL/NoSQL) to support analytics and modeling at scale.
- Develop monitoring dashboards and automated retraining workflows to maintain model accuracy.
- Experience ranges from 6-10 years in Python (Pandas, scikit-learn, PySpark) and SQL.
- Proven expertise in supervised and unsupervised ML techniques (regression, trees, clustering, neural nets) and advanced stats (hypothesis testing, time-series).
- Hands on experience with computer-vision and generative-AI projects.
- Familiarity with Docker, Kubernetes, and cloud ML platforms (Azure/AWS).
- Hands on experience in communicating updates and resolutions to customers and other partners and ability to translate data insights into business recommendations.
- Familiarity with BI tools (Tableau, Looker, Power BI) and MLOps frameworks (MLflow, Kubeflow).
- Familiarity with FastAPI for building and deploying model‐serving endpoints.
- Familiarity working with in Linux Environments.