- Collaborates with translators/SMEs/IT/data engineers to define technical problem statements and hypotheses to test; understands business problems to implement scalable and sustainable solutions.
- The business problems will be related to predicting the failure of the machines and estimating the useful life of the machines, which requires an understanding of analysis such as Vibration Analysis, Motor Circuit Analysis, Oil Analysis, and Infrared Thermography.
- Designs, creates, tests, and implements complex models and algorithms for predicting the machine failures
- Regularly tests and maintains analytical models to improve efficiency and keep up with changing business needs, ensuring timely analysis and testing for regular maintenance of solutions over time
- Writes reports articulating the analytics insights and their business impacts
- Conducts and leads meetings and workshops to explain findings
- Communicate results of the model to non-technical resources through various means including designing and building intuitive UI
- Support promoting data-driven decision making and advanced analytics techniques within Novelis
- Adhere to standards and best practices for performing APM projects
- Support building of accelerators for various APM solutions
Minimum Qualifications:
- 2-3 years of experience in designing, developing, testing, and implementing predictive models in a manufacturing setting.
- Should possess a strong ability to combine large volumes of disparate data sources and mine them for meaningful insight and to present the analysis findings to business stakeholders
- Strong hands-on experience in various data mining tools such as Databricks, Python, Power BI, Excel, and SQL
- Degree in electrical, mechanical, robotics, or related discipline
Preferred Qualifications:
- Experience in Predictive Maintenance technologies in manufacturing, specifically metals manufacturing
- Experience in building frontend solutions using JavaScript
- Understanding of operational technology (OT) architectures and Industry 4.0
- Master’s degree in Analytics, or another advance.