Key Responsibilities
· Analyse complex data in Logistics (Freight and Warehouse Materials Flow) to drive business process improvement decisions both internal logistics and cross functionally.
· Define and establish operational metrics through data-enabled insight and analysis.
· Establish data visualization and dashboards for both tactical operational management and manager’s view purposes.
· Provide user training in dashboards & data maintenance.
· Establish causal relationship with statistics and problem solve through data driven techniques.
· Collaborate with cross functional teams (Supply Chain, Manufacturing, Materials and Production Control) to understand end-to-end manufacturing order fulfilment data needs, identify problem statements and critical data points, establish metrics and dashboard to enable analytics insights and deep dives gaps analysis. Make recommendations on areas of improvement.
· Implement change and evaluate performance/metric data accuracy and effectiveness.
· Build models and methods to drive data connectivity and process automation.
· Lead assigned projects that require the ability to extract information from complex unstructured data.
· Act us Logistics SGP Analytics focal in partnership with Manufacturing to drives SMART Factory data connectivity initiatives.

Key Requirements
· Bachelor’s degree or higher in Industrial engineering, computer/data science or statistics.
· Experience with visual analytics platform (eg: Tableau), query languages (eg:SQL), pre-processing and statistical analysis such as Unix, Python, R program.
· Experience in data analysis in a business setting and deployment of improvement solutions.
· SAP EWM/ECC system experience preferred.
· Knowledge and understanding of manufacturing Logistics warehouse operations, supply chain / concepts and application.
· Strong analytical capabilities, with the ability to apply data science techniques and distill complex data into actionable operations improvement solutions.
· Ability to communicate data science solutions to business stakeholders in a business process improvement context.
· High learning agility in understanding new data science techniques in the logistics / manufacturing industry.
· Self-driven with the ability to work independently under pressure and adapt quickly to changing business priorities.
· Attention to details and high data accuracy.
· Ability to effectively work and collaborate with a culturally diversified cross functional team.

If you believe you fit the requirements for the role, please click Apply now. Alternatively, you can email your CV to gloria.xu@connexus-global.com or look me up on LinkedIn and message me there. Only shortlisted candidates will be notified.

Data provided is for recruitment purposes only. EA Licence Number: 18S9186. EA Registration Number: R1879945.

Data Scientist