Data Scientist - ML, Python

Job Summary

3. 🟢 Classical (Traditional) AI/ML Roles – Requirement Details3.1 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

• AWS3.4 Experience Requirement

• Minimum 7 years in AIML domain3.5 Key Clarification

• Deep learning / Gen AI skills not mandatory

Strong focus on production-grade ML solutions

Key Responsibilities

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Skill Requirements

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Other Requirements

3. 🟢 Classical (Traditional) AI/ML Roles – Requirement Details3.1 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

• AWS3.4 Experience Requirement

• Minimum 7 years in AIML domain3.5 Key Clarification

• Deep learning / Gen AI skills not mandatory

Strong focus on production-grade ML solutions