Walmart is hiring recent graduates for data analyst positions. Walmart is holding a hiring campaign off campus. Details, eligibility, and the job description at Walmart are provided below.
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About Walmart
With its headquarters located in Bentonville, Arkansas, Walmart Inc. is a multinational retail firm based in the United States that runs a chain of hypermarkets, also known as supercenters, cheap department stores, and grocery stores around the country. Sam and James “Bud” Walton, brothers, started the business in the neighbouring town of Rogers, Arkansas in 1962. On October 31, 1969, the corporation was registered under Delaware General Corporation Law. Additionally, it owns and runs the retail warehouses for Sam’s Club.
About Walmart
Job Role: Data Analyst
Company Website: www.walmart.com
Qualification: Any Graduates
Experience: Freshers (0-2 Years)
Batch: Recent Batches
Salary: As per company standards
Job Location: Bangalore
Last Date: ASAP
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Roles & Responsibilities
- Oversee machine learning end-to-end engineering solutions at scale.
- Create real things by incorporating data science solutions.
- Write well-written, effective code that scales to Wal-Mart
- Put ML models into production and address every model management issue.
- To take use of distributed infrastructure and drastically cut down on training time, parallelize algorithms and model training.
- Accept Wal-Mart’s quality requirements and create and suggest industry-wide process standards and best practices for the retail sector.
- Investigate, pick up, and modify new technology to address issues and enhance current ones.
- Take part in activities to develop creative solutions.
- Create, construct, test, and implement innovative solutions at scale that will affect millions of customers globally and extract value from data at Walmart Scale
- Engage with Walmart’s data science teams to learn about their main technical problems and develop and provide solutions.
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Required Skills & Qualifications
- 0–2 years of related experience after earning a bachelor’s
- Proficiency in Complex Problem Analysis and Data Science Algorithm Translation
- Strong familiarity with a number of key machine learning topics, including classification, forecasting, data/text mining, natural language processing, decision trees, random forests, adaptive decision algorithms, search algorithms, neural networks, and deep learning algorithms.
- Predictive and prescriptive analytics, web analytics, regression, time series, dynamic/causal models, statistical learning, guided decisions, and topic modelling are examples of prior statistical learning experience.
- Expertise in big data analytics: recognising patterns, trends, and anomalies in vast amounts of data; solid knowledge of Python and R.
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