Jobs Companies CHEP Specialist Data Analyst

À propos de ce poste Specialist Data Analyst chez CHEP

CHEP · Hybride · Madrid, Community of Madrid, Spain

CHEP helps move more goods to more people, in more places than any other organization on earth via our 347 million pallets, crates and containers. We employ approximately 13,000 people and operate in 60 countries. Through our pioneering and sustainable share-and-reuse business model, the world’s biggest brands trust us to help them transport their goods more efficiently, safely and with less environmental impact. 

What does that mean for you? You’ll join an international organization big enough to take you anywhere, and small enough to get you there sooner. You’ll help change how goods get to market and contribute to global sustainability. You’ll be empowered to bring your authentic self to work and be surrounded by diverse and driven professionals. And you can maximize your work-life balance and flexibility through our Hybrid Work Model.

Job Description

This role is critical to supporting data-driven decision-making by transforming complex data into actionable insights that improve business performance.
The position will analyse large volumes of data from multiple sources, providing meaningful recommendations to stakeholders and senior leaders.

Key Responsibilities May Include:

  • Analyze high-volume, complex data from multiple sources, using advanced tools and techniques to generate meaningful insights.
  • Develop and deliver sophisticated visualizations, dashboards, and reports that translate complex data into clear, actionable insights for business stakeholders.
  • Present findings and recommendations, simplifying complex analyses to provide clear and actionable insights that support business objectives.
  • Partner with cross-functional teams at all levels to standardize data analysis processes and improve data capture practices.
  • Use advanced analytics and machine learning techniques to perform deep-dive analysis and generate forward-looking insights.
  • Identify opportunities for digital transformation and develop innovative solutions to improve data capture, visualization, and reporting processes.
  • Ensure the accuracy, consistency, and quality of data by working closely with internal and external stakeholders.
  • Provide strategic guidance to senior leadership, leveraging data insights to drive business growth, enhance decision-making, and support long-term success.

  • Define new analytical methodologies to solve business problems.

  • Use machine learning algorithms to find opportunities.

  • Find solutions to complex business problems using data.

  • Lead the analytical approach with state-of-the-art technical solutions.

  • Define analytical best practices.

  • Use advanced analytics to be able to predict future opportunities for Asset Control

  • Cover analyses regarding all programs and regions Asset Productivity covers.

  • Help drive the strategy of the area answering business questions.
     

Experience

  • Strong python skills applied to analysis.

  • Experience working with complex coding frameworks.

  • Experience in finding business opportunities.

  • Knowledge on cloud computing environments.

  • Ability to analyse, model and interpret data.

  • Relational databases knowledge (SQL).

  • Experience transforming data into insights.

  • Experience designing visual presentations to tell the story behind the data.

  • Experience understanding complex data patterns.

  • Experience applying machine learning to solve business problems.

  • Statistics

  • Proved experience organizing own tasks (manage priorities, standardization, automation, troubleshooting and short-term planning).

  • Experience with change management.
     

Skills and Knowledge

  • Strong mathematical and statistical background

  • Strong service orientation.

  • Autonomous and capable to lead projects.

  • Strong analytic skills.

  • Can act under time pressure and interact with senior level stakeholders.

Remote Type

Hybrid Remote

Skills to succeed in the role

Adaptability, Critical Thinking, Data Analytics, Data Visualization, Empathy, Experimentation, Microsoft Power Business Intelligence (BI), Python (Programming Language), Regression Analysis, R Programming, SQL Tools, Tableau (Software), Taking Ownership, Teamwork, Understand Customers

We are an Equal Opportunity Employer, and we are committed to developing a diverse workforce in which everyone is treated fairly, with respect, and has the opportunity to contribute to business success while realizing his or her potential. This means harnessing the unique skills and experience that each individual brings and we do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state, or local protected class.

Individuals fraudulently misrepresenting themselves as Brambles or CHEP representatives have scheduled interviews and offered fraudulent employment opportunities with the intent to commit identity theft or solicit money. Brambles and CHEP never conduct interviews via online chat or request money as a term of employment. If you have a question as to the legitimacy of an interview or job offer, please contact us at [email protected].

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À propos de CHEP

CHEP helps move more goods to more people, in more places than any other organization on earth via our 347 million pallets, crates and containers. We employ approximately 13,000 people and operate in 60 countries. Through our pioneering and sustainable share-and-reuse business model, the world’s biggest brands trust us to help them transport their goods more efficiently, safely and with less environmental impact. What does that mean for you? You’ll join an international organization big enough to take you anywhere, and small enough to get you there sooner. You’ll help change how goods get to market and contribute to global sustainability. You’ll be empowered to bring your authentic self to w

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