Senior Data Scientist & Agentic AI
CirrusLabsBangalore (division)20 hours ago
Job descriptionSelect appropriate evaluation metrics based on business goals and problem types : Classification : Accuracy, Precision, Recall, F1-score, ROC-AUC, PR-AUC, Log Loss, Cohen's Kappa, Matthews Correlation Coefficient. Regression : RMSE, MAE, R2, Adjusted R2, MAPE, SMAPE. Ranking / Recommenders : NDCG, MAP@K, Recall@K, Hit Rate. Clustering : Silhouette score, Davies-Bouldin Index, Calinski-Harabasz score. Forecasting : MSE, RMSE, MAPE, sMAPE, Theil's U statistic. Perform cross-validation , bootstrapping , and A / B testing for robust model validation. Monitor model drift, bias, and fairness across data slices. Stay current with research trends in ML, DL, and applied AI (e.g., transformer models, self-supervised learning, and causal inference). Conduct experiments to improve baseline models using new architectures or ensemble approaches. Document hypotheses, results, and model interpretation clearly for cross-functional collaboration. Education : Master's or Bachelor's in Computer Science, Mathematics, Statistics, Data Science, or a related quantitative discipline. Experience : 6–7 years in core data science or applied ML, with end-to-end project ownership. Programming : Proficient in Python (pandas, NumPy, scikit-learn, statsmodels, XGBoost, LightGBM, TensorFlow / PyTorch). Data Handling : Strong in SQL and data wrangling with large-scale structured and unstructured datasets. Mathematics & Statistics : Excellent foundation in probability, linear algebra, optimization, and hypothesis testing. Model Evaluation : Proven expertise in selecting and interpreting metrics aligned to business goals. Visualization : Skilled in Matplotlib, Seaborn, Plotly , and storytelling with data-driven insights . Experience with MLOps , A / B testing , and data versioning tools (e.g., DVC, MLflow). Knowledge of causal inference , Bayesian modeling , and Monte Carlo simulations . Familiarity with transformer-based models (BERT, GPT, etc.) for NLP tasks. Hands-on experience with graph analytics or network science . Experience mentoring junior data scientists and reviewing model design. Exposure to cloud ML stacks (AWS Sagemaker, GCP Vertex AI, or Azure ML Studio). Strong analytical thinking and problem-solving orientation. Ability to balance scientific rigor with business pragmatism. Excellent communication — both technical and non-technical audiences. Curious, self-driven, and comfortable working in fast-paced environments.
Experience : 5 years
Notice Period : Immediate joiner
Job Location : Bangalore (Hybrid)
Job Description : Key Responsibilities
Core Modeling & Algorithmic Work
- Develop and optimize models for classification, regression, clustering, forecasting, and recommendation systems .
- Use a range of algorithms such as :
- Regression Models : Linear, Ridge, Lasso, ElasticNet, Quantile, Poisson, etc.
- Classification Models : Logistic Regression, Decision Trees, Random Forests, XGBoost, LightGBM, SVM, Neural Networks, etc.
- Unsupervised Learning : K-Means, DBSCAN, Hierarchical clustering, PCA, t-SNE, Autoencoders.
- Time Series & Forecasting : ARIMA, SARIMA, Prophet, LSTM, and hybrid models.
- Recommendation Systems : Collaborative filtering, Matrix factorization, Content-based and hybrid approaches.
Evaluation Metrics & Model Assessment
Research & Experimentation
Required Skills & Qualifications
Nice to Have
Soft Skills
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Senior Data Scientist • Bangalore (division)
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