Data Scientist1-2

Key Skills

Data science techniques, Data Visualization, KPIs, Machine learning techniques, Python Programming, SQL, Supply Chain Management, Tableau

Job Description

Data Scientist to collaborate with Data Analytics Engineers in delivering advanced insights

And predictive analytics for supply chain operations.

 This role

Involves leveraging statistical models, machine learning algorithms, and data visualization

Techniques to generate actionable insights that drive operational efficiency and strategic decision-making.

The ideal candidate will have a strong background in data science, predictive modeling, and Supply chain analytics, along with expertise in Python, SQL, Tableau

Key Responsibilities:

Advanced Analytics & Insights Generation

• Develop predictive models and statistical analyses to identify patterns, trends, and anomalies in supply chain data.

• Partner with Data Analytics Engineers to create machine learning models that support key metrics such as on-time in full (OTIF), on-time delivery (OTD),

• Forecasting, inventory optimization etc

• Build and maintain dynamic dashboards in Tableau to visualize insights, KPIs, and metrics for supply chain stakeholders.

• Conduct root cause analyses to identify process inefficiencies, bottlenecks, and areas For improvement.

Data Collaboration & Model Deployment

• Collaborate with cross-functional teams (supply chain ops, solution leads, analytics engineers) to understand business needs and translate them into data-driven Solutions.

• Work closely with Analytics Engineers to optimize data pipelines and ensure model outputs are integrated into reporting platforms and operational workflows.

• Deploy machine learning models into production environments and continuously monitor performance to ensure accuracy and effectiveness.

Innovation & Process Improvement

• Drive innovation by exploring emerging technologies, advanced analytics techniques, and automation solutions.

• Identify opportunities for process optimization, leveraging insights to inform strategic initiatives and improve supply chain efficiency.

• Ensure that data-driven solutions align with best practices in data governance, data privacy, and compliance

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