DTICI_Data - Quality Management and Emerging Tech#Consultant_T9
Bengaluru, Karnataka, India
INR 1400K-2000K (estimate) Mid-level Full Time
Tasks
- Analyze BMS data for SOC SOH and charging degradation
- Build classical machine learning models for battery anomaly detection
- Collaborate on data pipelines for telematics and battery datasets
- Conduct root cause analysis using clustering and PCA
- Create diagnostic dashboards and KPIs for battery health
- Develop time series models for early detection of battery instability
- Perform feature engineering and statistical analysis for battery sensors
- Support model deployment to cloud or on prem execution
Perks/Benefits
- N/A
Skills/Tech-stack
Anomaly Detection | Azure Data | Azure Data Factory | Azure Databricks | Azure ML | Clustering | Component analysis | Data Analysis | Data Factory | Data cleaning | Decision Trees | Exploratory Data Analysis | Feature Engineering | Git | Gradient boosting | Jupyter | MLOps | Machine Learning | NumPy | Outlier Detection | Pandas | Plotly | Power BI | Principal Component Analysis | Python | Random Forest | Regression | SQL | SciPy | Scikit-learn | Series analysis | Signal Processing | Statistical modeling | Support Vector Machines | Time Series | Time Series Analysis | Vector machines
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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