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"domain_id": "data_science",
"display_name": "Data Science & Analytics",
"description": "Machine Learning, Data Analysis, AI Research, and Business Intelligence",
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"trained neural networks for image classification",
"implemented NLP models using transformers and BERT",
"designed feature engineering pipelines for ML",
"built recommendation systems using collaborative filtering",
"deployed ML models to production with MLflow",
"created interactive dashboards in Tableau",
"performed A/B testing with statistical significance analysis"
],
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"reduced model training time by 60% using distributed computing",
"diagnosed and fixed data leakage in ML pipeline",
"optimized hyperparameters using Bayesian optimization",
"handled class imbalance with SMOTE and weighted sampling",
"debugged data quality issues affecting model performance",
"designed experiment to measure causal impact of recommendation",
"created automated anomaly detection system",
"resolved data drift issues in production models",
"built interpretable models for regulatory compliance"
],
"leadership": [
"led data science team of 4 on personalization project",
"presented ML insights to C-level stakeholders",
"coordinated with engineering for model deployment",
"organized data science reading group in company",
"mentored junior analysts on SQL and Python",
"drove adoption of MLOps best practices",
"led cross-functional project with marketing team",
"managed data labeling team for annotation project",
"conducted training sessions on Pandas for analysts",
"championed experiment-driven decision making culture"
],
"internship_experience": [
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"ML research intern at Google Brain working on NLP",
"analytics intern at McKinsey for retail optimization",
"AI intern at NVIDIA on computer vision projects",
"research intern at IISc on deep learning",
"data analyst intern at Zomato for demand forecasting",
"business intelligence intern at Amazon building dashboards",
"ML platform intern at Meta for model serving",
"quantitative research intern at Goldman Sachs",
"applied scientist intern at AWS on personalization"
]
},
"industry_benchmarks": {
"min_employability_score": 0.65,
"expected_cgpa": 8.0,
"expected_internship_months": 4,
"critical_skills": [
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"ml_fundamentals"
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"nice_to_have_skills": [
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},
"skill_gaps_mapping": {
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"courses": [
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"Fast.ai",
"Stanford CS231n"
],
"certifications": [
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"PyTorch Certified"
]
},
"mlops": {
"demand_score": 0.75,
"courses": [
"MLOps Specialization",
"ML Engineering for Production"
],
"certifications": [
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"GCP ML Engineer"
]
},
"statistics": {
"demand_score": 0.70,
"courses": [
"Statistics for Data Science",
"A/B Testing Masterclass"
],
"certifications": []
},
"big_data": {
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"courses": [
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"Databricks Academy"
],
"certifications": [
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]
}
},
"detection_keywords": [
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]
} |