Data Scientist

Cognizant; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

A leading technology consulting company is seeking an experienced Data Scientist specializing in Supply Chain. The role involves analyzing complex datasets, developing predictive models, and collaborating across departments to enhance supply chain efficiency. Ideal candidates will have over 14 years of experience in Data & Analytics, a strong background in life sciences, and proficiency in data technologies like Hadoop and Python. This position offers a dynamic work environment and opportunities for innovation in analytics.

Qualifications

• 14+ years of experience in Data & Analytics, with strong focus on Life Sciences Supply Chain.
• Hands-on experience with big data technologies and cloud-based platforms.
• Proficiency in Databricks, Python, R, and AWS/Azure services.
• Deep understanding of pharmaceutical supply chain processes.
• Familiarity with data visualization tools and supply chain planning systems.
• Knowledge of regulatory compliance and working with structured and unstructured data.

Responsibilities

• Analyze large datasets from ERP, MES, and LIMS systems for actionable insights.
• Develop predictive models and algorithms for supply chain optimization.
• Collaborate with teams to address operational challenges with analytics solutions.
• Implement data governance practices to ensure data integrity.
• Create dashboards and reports for real-time supply chain monitoring.
• Stay updated on developments in AI/ML for supply chain analytics.

Skills

Data Analysis

Model Development

Cross-Functional Collaboration

Data Governance

Machine Learning

Cloud Computing

Data Visualization

Tools

Hadoop

Python

R

AWS

Azure

Power BI

Tableau

SAP IBP

Job description

Data Scientist JD for Supply Chain

Key Responsibilities

• Supply Chain Data Analysis and Interpretation, analyze large and complex datasets from ERP, MES, and LIMS systems to identify trends, patterns, and actionable insights for improving demand forecasting, inventory optimization, and cold chain logistics.
• Model Development for Supply Chain Optimization – develop and validate predictive models and algorithms for demand sensing, capacity planning, lot traceability, and risk mitigation across global pharmaceutical supply chains.
• Cross‑Functional Collaboration – work closely with manufacturing, quality, clinical supply, and distribution teams to understand operational challenges and deliver tailored analytics solutions that ensure compliance with GxP and regulatory standards.
• Data Management & Compliance – implement robust data governance practices to maintain data integrity and quality, ensuring adherence to FDA, EMA, and other regulatory requirements for life sciences operations.
• Reporting and Visualization – create intuitive dashboards and reports for real‑time supply chain monitoring, leveraging tools like Power BI, Tableau, or Spotfire to communicate insights to stakeholders.
• Innovation in Supply Chain Analytics – stay updated on the latest developments in AI/ML for supply chain, including digital twin modeling, predictive maintenance, and blockchain for serialization, applying innovative techniques to solve complex challenges.

Preferred Qualifications

• 14+ years of experience in Data & Analytics, with a strong focus on Life Sciences Supply Chain.
• Hands‑on experience with big data technologies (Hadoop, PySpark) and cloud‑based analytics platforms (AWS, Azure).
• Proficiency in Databricks, Python, R, and AWS/Azure services such as SageMaker, Glue, Lambda, Step Functions, and EMR.
• Deep understanding of pharmaceutical supply chain processes, including cold chain logistics, serialization, and clinical trial supply.
• Familiarity with data visualization tools (Tableau, Power BI) and supply chain planning systems (SAP IBP, Kinaxis).
• Knowledge of regulatory compliance (GxP, FDA, EMA) and experience working with structured and unstructured data from ERP and manufacturing systems.