Firm Name: Walmart

Numbers of Jobs: Senior Data Analyst

Education Need: Graduate

Job Hours: 8

Payment: $20-$30/Hours

What's Job City: DALLAS

Job Details:

You're going to act.

•  In order to provide actionable, customer-centric insights and help retailers and suppliers make better business decisions regarding the performance of omni channel 360, Data Ventures, a lean startup incubated within Walmart, is developing the best-in-class suite of Data Products.
•  As a Senior Data Analyst, you will play a crucial technical role in the creation of data-centric insights and product features. You will achieve outstanding business outcomes with the assistance of the product's key stakeholders.
•  A system must have SQL, Python, R, Looker, PowerBI, SQL, NoSQL, Big Data, and cloud technologies like GCP BQ in order to be taken into account.

 You'll carry out:.

•  Develop appropriate methodologies and identify statistical techniques to address business needs; translate complex business requirements into concise, understandable data analysis plans.
•  Analyze a lot of data from various sources to find trends, patterns, and insights that have a positive impact on the business.
•  Make and keep up dashboards, reports, and visualizations that give stakeholders a comprehensive view of business performance.
•  Work closely with other team members to plan and complete data analysis projects.
•  Collaborate with other teams, such as product management and data science, to understand their data requirements and provide data-driven insights to inform decision-making.
•  To ensure your data's accuracy and quality, develop and implement data management policies and procedures.
•  Participate in developing the methodologies, tools, and best practices for data analytics.
•  Clear communication of insights and recommendations to business stakeholders can be achieved through the use of visualizations, presentations, and other storytelling techniques.
•  Participate in the creation of the data ecosystem strategy, which includes, among other things, scalability, storage, accessibility, and standards for data quality.

 What You Should Bring Is.

•  data expertise, a data-driven mindset, and a love of problem-solving.
•  Possessing the abilities to play around with large amounts of data and the ability to write SQL, Python, R, or equivalent code for data analysis and pattern recognition.
•  having experience using distributed datastores (e. g. , SQL, and NoSQL), in addition to cloud computing tools like GCP BQ.
•  understanding of best practices for and familiarity with visualization tools like Looker, PowerBI, etc.
•  a track record of analyzing sizable datasets, identifying trends, and telling stories with the data.
•  The preference is to have prior knowledge of working with the retail data sets.

 Essential Conditions.

•  Below is a list of the minimum requirements for this position. In the absence of any prerequisites being listed, none exist.
•  Option 1: Bachelor's degree in business, engineering, statistics, economics, analytics, mathematics, the arts, finance, or a field closely related, plus two years of experience in data analysis, data science, statistics, or a field closely related. A master's degree in business, engineering, statistics, economics, analytics, mathematics, computer science, information technology, or a related field is the second choice. Option 3: Four years of expertise in data science, statistics, data analysis, or a related field.

 Preferred credentials.

•  Below is a list of the position's optional and preferred requirements. If none are listed, no preferred credentials exist.
•  Data science, data analysis, statistics, or related field; Master's degree in business, computer science, engineering, statistics, economics, analytics, mathematics, computer science, information technology, or related field; Related industry experience (for example, retail, merchandising, healthcare, eCommerce); Successful completion of assessments in data analysis and business intelligence tools and scripting languages (for example, SQL, Python, Spark, Scala, R, Power);