Data Analyst – Logistics Business Improvement
Job Location:
Job Location:
Houston, MS - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
22 days ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Role- Data Analyst Logistics Business Improvement
Location- Houston TX Onsite
Location- Houston TX Onsite
Job Type- 12 month contract
Looking for a Data Analyst who can turn logistics data into something more useful than a weekly spreadsheet nobody trusts but everyone keeps forwarding around anyway.
This role sits right in the middle of logistics transportation supply chain operations and analytics. The team needs somebody who can build meaningful reporting spot operational issues early and help leadership actually see whats happening across transportation costs carrier performance and logistics operations in real time.
A big part of the work revolves around Power BI SAP data analytics development KPI tracking and process improvement across global logistics operations. Theres also a strong business-facing side to the role so this is not just a sit quietly and build dashboards position.
Youll be working closely with logistics teams supply chain stakeholders and IT groups to improve reporting visibility support transportation analytics and help drive operational improvements across multiple workstreams.
What matters most for this role:
Strong Power BI experience
SAP experience ideally around logistics or supply chain operations
Experience with SQL DAX Power Query and advanced analytics
Ability to build dashboards KPIs and reporting frameworks that people actually use
Commercial supply chain or logistics experience
Strong analytical and root cause analysis skills
Ability to work directly with business stakeholders and translate operational needs into reporting solutions
Experience with Alteryx Tableau SharePoint SAP S/4 HANA transportation analytics or oil & gas logistics environments is a strong plus.
The team is looking for somebody whos naturally curious comfortable digging through messy operational data and able to explain findings without sounding like they swallowed a reporting manual. Somebody who can spot patterns challenge bad assumptions and help improve processes instead of just documenting them after the fact.
Looking for a Data Analyst who can turn logistics data into something more useful than a weekly spreadsheet nobody trusts but everyone keeps forwarding around anyway.
This role sits right in the middle of logistics transportation supply chain operations and analytics. The team needs somebody who can build meaningful reporting spot operational issues early and help leadership actually see whats happening across transportation costs carrier performance and logistics operations in real time.
A big part of the work revolves around Power BI SAP data analytics development KPI tracking and process improvement across global logistics operations. Theres also a strong business-facing side to the role so this is not just a sit quietly and build dashboards position.
Youll be working closely with logistics teams supply chain stakeholders and IT groups to improve reporting visibility support transportation analytics and help drive operational improvements across multiple workstreams.
What matters most for this role:
Strong Power BI experience
SAP experience ideally around logistics or supply chain operations
Experience with SQL DAX Power Query and advanced analytics
Ability to build dashboards KPIs and reporting frameworks that people actually use
Commercial supply chain or logistics experience
Strong analytical and root cause analysis skills
Ability to work directly with business stakeholders and translate operational needs into reporting solutions
Experience with Alteryx Tableau SharePoint SAP S/4 HANA transportation analytics or oil & gas logistics environments is a strong plus.
The team is looking for somebody whos naturally curious comfortable digging through messy operational data and able to explain findings without sounding like they swallowed a reporting manual. Somebody who can spot patterns challenge bad assumptions and help improve processes instead of just documenting them after the fact.
Regards
Himanshu Rawat
