Data Scientist

Role Purpose

To design, develop, and deploy advanced machine learning (ML) and statistical models that transform structured, semi-structured, and unstructured data into actionable insights. This role will support business functions such as farming, factory operations, supply chain, finance, and sustainability.

Key Responsibilities

· Model Development: Build predictive and prescriptive ML models (time-series, regression, classification, clustering, optimization).

· Feature Engineering: Extract, transform, and engineer features from diverse data (ERP, IoT, sensors, finance, external datasets).

· Data Management: Collect, clean, and validate large datasets from multiple internal and external systems.

· Deployment: Deploy models into production environments with MLOps practices (CI/CD, retraining pipelines).

· Collaboration: Partner with Product Managers, Data Engineers, and Business Analysts to align AI solutions with BU requirements.

· Monitoring: Continuously track model accuracy, fairness, and drift; retrain and recalibrate models as required.

· Governance: Adhere to Responsible AI guidelines, ensuring transparency, fairness, and explainability of ML models.

Required Qualifications

· Bachelor, masters degree in data science, Computer Science, Statistics, Applied Mathematics, or related.

· 37 years of proven experience in applied data science.

· Strong programming skills in Python, R, SQL.

· Hands-on experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn.

· Strong statistical and mathematical modeling background.

· Experience with data visualization tools (Tableau, Power BI, matplotlib, seaborn).

· Familiarity with cloud platforms (AWS, Azure, GCP).