What it’s like working at Walmart within Data Analytics with Ajay Yvs
Ajay Yvs has been working as a Data Analyst at Walmart for almost 7 years. He comes on the podcast to discuss some of the projects that he’s worked on while there. Ajay gives us an insight into some of the website changes he’s made while optimizing the analytics on the platform. Ajay also discusses ways a young data analyst can stand out in their career.
You can connect with him on LinkedIn here.
Listen to the Podcast Here, or Find it Wherever You Get Your Podcasts:
Here are Five Things We Cover:
- Onboarding sellers quickly and improving their satisfaction were the main focuses when Ajay joined Walmart. The metrics that were prioritized included reducing onboarding time and increasing seller satisfaction.
- Special projects, dashboarding, and product analytics were the three types of projects that Ajay worked on. Special projects involved analyzing data to prioritize features, dashboarding projects focused on store launch and drone delivery eligibility, and product analytics projects provided ongoing reporting and answered business questions.
- Ajay emphasized the importance of understanding the framework and knowing the data sources when working on analytics projects. They also highlighted the need to work closely with data engineers to determine the best way to present the data for analysis.
- Soft skills, problem-solving abilities, and a broad understanding of data science and engineering concepts are important in the field of data analytics. Technical skills like SQL are still valuable, but the expectation is for data analysts to be generalists and identify the best solutions for each problem.
- Collaboration and frequent interaction with stakeholders were highlighted as crucial for successful data analytics projects. Ajay emphasized the iterative approach to problem-solving and the importance of continuous improvement based on feedback from sellers and other stakeholders.
Here are Three Key Takeaways From This Episode
Embrace a Framework Approach to Problem-Solving:
The first key takeaway from the episode is the significance of using frameworks to tackle analytical challenges. Ajay highlights the importance of identifying and understanding the problem at hand before diving into the metrics and analysis. Different frameworks, such as lean startup or defining measure and control, can be employed based on the specific problem. By adhering to a structured approach, data analysts can minimize wasted effort and maximize the effectiveness of their analysis. Additionally, Ajay encourages an iterative problem-solving process that allows for tackling one variable at a time or using a multi-layered approach.
Actionable Advice: Adopt and adapt relevant problem-solving frameworks to guide your analysis. Consider the problem’s context, break it down into manageable components, and identify the ideal analytical approach for each stage.
Nurture Soft Skills for Effective Collaboration:
The second takeaway emphasizes the importance of soft skills in analytics roles. While technical competence is vital, collaboration, problem-solving, and a strong understanding of data science concepts are equally significant. Ajay highlights the communication and collaboration required with stakeholders, emphasizing the need to differentiate between what a stakeholder wants versus what they truly need. Being able to navigate these conversations effectively is essential for aligning the analytical approach with the strategic objectives of the project.
Actionable Advice: Prioritize the development of soft skills alongside technical expertise. Sharpen your problem-solving abilities, practice effective communication, and deepen your understanding of data science and engineering concepts.
Leverage Data and Feedback for Continuous Improvement:
The final takeaway showcases the power of data and feedback in driving continuous improvement within e-commerce analytics. Ajay shared his experience in onboarding sellers onto a platform, utilizing data sets to analyze each step’s efficiency and comparing them with competitor platforms. By actively collecting feedback from sellers, they were able to identify pain points and make necessary improvements to streamline the onboarding process. This iterative approach ensures that seller satisfaction continually improves while reducing onboarding time.
Actionable Advice: Harness the power of data to identify bottlenecks, optimize processes, and enhance the overall user experience. Regularly collect and analyze feedback from users to iterate and improve your analytical solutions.