E-Commerce Data Analyst (Category / Supply Chain)

As an E-Commerce Data Analyst in the E-commerce Category & 4P Analytics Team, you'll tackle the most pressing and intriguing e-commerce challenges in category and supply chain domain, and will contribute to shaping HP’s e-commerce future. Our dynamic, highly skilled, and diverse global team is dedicated to data-driven problem-solving. In this role, you'll combine your analytical prowess, technical skills, creativity and stakeholder engagement to innovate in HP’ e-commerce strategies.

If you are passionate about data and analytics, and driving business growth through strategic pricing initiatives, we encourage you to apply for this exciting opportunity.

About You:

• You are data-driven, with a passion for identifying patterns and insights, and driving these insights into action.
• You excel at simplifying complex processes and making them more efficient.
• You are solution-oriented: you see problems as puzzles and are relentless in solving them.
• You are eager to learn and grow.

Key Responsibilities:

• Analytics: Conduct detailed data analysis to generate actionable insights that support decision-making across various business functions in e-commerce. Conduct exploratory data analysis and deep dives to identify trends, anomalies, and opportunities for optimization across various domains, including marketing, operations, and finance.
• Data Transformation & Cleaning: Develop scripts and workflows using Python and SQL to clean, process, and transform large datasets from multiple sources into structured formats suitable for analysis. Ensure adherence to data governance policies by validating data accuracy, consistency, and completeness across datasets and reports.
• Data Visualization: Create impactful, visually compelling dashboards and reports in Tableau, translating complex data into clear insights for non-technical stakeholders.
• Collaboration with Engineering & Business Teams: Work closely with data engineers, business analysts, and product teams to define data requirements and ensure alignment with business objectives.
• Automation & Optimization: Leverage Python scripting and SQL to automate routine reporting tasks and optimize data retrieval and analysis workflows, improving efficiency and reducing manual effort.

Requirements:

• Technical Proficiency:
  • SQL: Advanced proficiency in writing complex queries, data manipulation, and optimization for large datasets.
  • Python: Strong experience in data analysis libraries (e.g., pandas, NumPy), and automation of data processing tasks.
  • Git: Familiarity with Git for version control and collaborative coding environments.
  • Tableau: Expertise in creating interactive, dynamic, and visually appealing dashboards and reports.
• Analytical Skills: Strong analytical and problem-solving skills, with the ability to draw insights from complex data sets.
• Business Acumen: Ability to understand business processes and translate them into technical data requirements.
• Attention to Detail: Rigorous approach to data accuracy and integrity in reporting and analysis.
• Communication: Strong verbal and written communication skills, able to explain technical concepts to non-technical stakeholders.

Bonus Points:

• Industry sector experience related to the position (e.g., retail, e-commerce, supply chain) is advantageous.
• Experience with data science/statistical modeling techniques.
• Project management certifications: PMI, Agile.
• Knowledge of Databricks.
• Experience with Git.

What We Offer:

• Opportunity to work in an international organization with colleagues from all over the world.
• Diverse, continued internal growth and career opportunities, including access to HP’s own learning platform and LinkedIn Learning.
• An attractive benefits package.
• Participation in our fantastic global business networks such as Women, Pride, Young Employees, and Disability.
• Time and resources dedicated to community contribution through Corporate Volunteering activities.

Scope & Impact

• Collaborates with peers, junior engineers, data scientists and project team.
• Typically interacts with high- level Individual Contributors, Managers, Directors and Program Core Teams.

Education & Experience

• Master's degree in relevant fields.
• 3-5 years’ related experience.