Data Scientist

Cognizant; Singapore; On-site; SGD 100,000 - 130,000; Full time

Job summary

A global technology and consulting firm is seeking a Data Scientist for Supply Chain in Singapore. Ideal candidates should have over 14 years of experience in Data & Analytics with a focus on life sciences. Responsibilities include analyzing large datasets, developing predictive models, and creating dashboards for monitoring supply chain performance. Proficiency in big data technologies, cloud platforms, and data visualization tools is essential. The role will require collaboration with cross-functional teams to innovate and implement analytics solutions compliant with regulatory standards.

Qualifications

• 14+ years of experience in Data & Analytics with life sciences focus.
• Hands-on experience with big data technologies and cloud-based analytics.
• Proficiency in data visualization and supply chain planning systems.

Responsibilities

• Analyze large datasets for improving demand forecasting and inventory optimization.
• Develop predictive models for supply chain processes.
• Create dashboards for real-time supply chain monitoring.

Skills

Data & Analytics

Supply Chain Optimization

Predictive Modeling

Cross-Functional Collaboration

Data Governance

Reporting

AI/ML Innovations

Tools

Hadoop

Power BI

Python

AWS

Tableau

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.