Back
Broad ML/cloud requirements, popular data role and likely metro hiring increase applicant competition.
Core ML/data skills are transferable, though telematics and automotive experience increase domain specificity.
Mandatory ML/cloud stack and degree requirements create moderate screening without explicit years requirement.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and deploy machine learning and deep learning models using Telematics/time series data to solve business challenges in automotive domain.
Perform comprehensive data preparation, exploratory data analysis, feature engineering, and model pipeline setup including hyper-parameter tuning and validation.
Create detailed reports and visualizations to communicate insights, collaborating with domain experts and leveraging cloud platforms for model deployment.
Degree required: B.E./B.Tech/M.Tech/M.Sc. in any stream.
Work Experience Required: Not explicitly mentioned in the JD.
Strong proficiency in Python programming and libraries (pandas, numpy, matplotlib, sklearn).
Experience with machine learning algorithms and cloud platforms (AWS, Azure, GCP).
Experienced with time-series/IoT data analytics, preferably involving automotive Telematics and Controller Area Network (CAN) protocols.
Capable of handling end-to-end machine learning model lifecycle including MLOps and model deployment in production environments.
Skilled in advanced data visualization and big data technologies such as Databricks, Spark, Tableau, or PowerBI.