As a Data Scientist within the Data & Artificial Intelligence division, you will design, develop, and deploy machine learning models and advanced analytics solutions using Python, Dataiku, and Azure Databricks. The role focuses on transforming data into actionable insights, operationalizing AI solutions, and delivering measurable business value through scalable and production-ready data science solution.
Qualifications & Experience
Minimum Qualification
- Bachelor's degree in Computer Science, Information Systems, Data Science, Statistics, Mathematics, Engineering, or a related field (Master's preferred).
- 5+ years of hands-on experience in Data Science, Machine Learning, Predictive Analytics, and AI solution development.
Experience
- Strong programming expertise in Python, including Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, and PyTorch.
- Hands-on production experience with Dataiku for data preparation, feature engineering, model development, deployment, automation, and monitoring.
- Experience with Azure Databricks, PySpark, MLflow, and large-scale distributed data processing.
- Strong SQL skills with experience working on large-scale structured and unstructured datasets.
- Deep understanding of Machine Learning, Statistical Modeling, Predictive Analytics, Data Mining, Feature Engineering, Model Validation, Hyperparameter Optimization, and Model Explainability.
- Experience developing and deploying Regression, Classification, Clustering, Forecasting, Recommendation, Customer Segmentation, Risk, and Fraud Detection models.
- Hands-on experience in NLP, Text Analytics, Sentiment Analysis, Generative AI.
- Proven experience in deploying and managing machine learning models in production using MLflow, Databricks Model Serving, Azure ML.
- Experience with MLOps practices, including CI/CD pipelines, model versioning, experiment tracking, model registry, automated retraining, model monitoring, drift detection, performance optimization, and Model governance.