Data Scientist Senior Advisor

Develop and deliver machine learning models including forecasting, classification, recommendation, clustering, and anomaly detection from data understanding through deployment support and continuous improvement.

Collaborate with clients and consultants to translate business problems into analytical tasks and communicate model insights effectively for business relevance.

Partner with data engineering and architecture teams to access and prepare data, use platforms like Snowflake, Databricks, and Microsoft Fabric, and implement MLOps practices for reproducible and monitored model deployment.

6-10 years of commercial experience in Data Science, Machine Learning or Advanced Analytics roles.

Strong hands-on experience with Python (including Scikit-Learn and at least one of XGBoost, LightGBM, TensorFlow, or PyTorch) and strong SQL skills with complex datasets.

Solid understanding and practical experience across supervised and unsupervised learning, statistical modeling, feature engineering, model evaluation, validation, and deployment.

Work Experience Required: 6-10 years in relevant roles; Notice Period: Not explicitly mentioned in the JD.

Experienced in delivering machine learning solutions from exploratory analysis to production or pilot deployment with strong focus on model governance and explainability.

Comfortable working in interdisciplinary teams bridging business and technical domains, able to translate ambiguous business needs into concrete analytical outputs.

Practiced in using cloud-based data platforms and MLOps processes to ensure reproducibility, monitoring, and continuous model improvement.