Job Summary
3. 🟢 Classical (Traditional) AI/ML Roles – Requirement Details
3.1 Mandatory Skills
Candidates must have strong expertise in:
- Statistical inference
- Exploratory Data Analysis (EDA)
- Feature engineering & feature selection
- Data transformation, scaling, and outlier detection
3.2 ML Techniques & Algorithms
- Model selection and model building
- Ensembling techniques
- Evaluation metrics
- Algorithms:
- Linear regression
- Logistic regression
- Random forest
- Decision trees
- Gradient boosting methods
3.3 Deployment / Platform Skills
- Model deployment and monitoring (drift detection)
- Hands-on experience with:
- Databricks
- AWS
3.4 Experience Requirement
- Minimum 7 years in AIML domain
3.5 Key Clarification
- Deep learning / Gen AI skills not mandatory
Strong focus on production-grade ML solutions
Key Responsibilities
Skill Requirements
Other Requirements
3. 🟢 Classical (Traditional) AI/ML Roles – Requirement Details
3.1 Mandatory Skills
Candidates must have strong expertise in:
- Statistical inference
- Exploratory Data Analysis (EDA)
- Feature engineering & feature selection
- Data transformation, scaling, and outlier detection
3.2 ML Techniques & Algorithms
- Model selection and model building
- Ensembling techniques
- Evaluation metrics
- Algorithms:
- Linear regression
- Logistic regression
- Random forest
- Decision trees
- Gradient boosting methods
3.3 Deployment / Platform Skills
- Model deployment and monitoring (drift detection)
- Hands-on experience with:
- Databricks
- AWS
3.4 Experience Requirement
- Minimum 7 years in AIML domain
3.5 Key Clarification
- Deep learning / Gen AI skills not mandatory
Strong focus on production-grade ML solutions