Walmart Hiring For 2024 | Data Analyst, Data Analytics | Apply Here !!

Responsibilities:

1. Manage end-to-end engineering solutions for Machine Learning at scale, ensuring seamless integration of data science solutions into tangible products.
2. Write efficient and high-quality code capable of functioning at Walmart scale.
3. Productionize ML models and address all model management challenges.
4. Parallelize algorithms and model training to leverage distributed infrastructure and reduce training time significantly.
5. Uphold Walmart’s quality standards and develop and recommend process standards and best practices across the retail industry.
6. Research, learn, and adopt new technologies to solve problems and enhance existing solutions.
7. Participate in events to develop innovative solutions.
8. Design, build, test, and deploy cutting-edge solutions at scale, impacting millions of customers worldwide and driving value from data at Walmart scale.
9. Collaborate with data science groups across Walmart to understand their major engineering challenges and propose solutions.
10. Identify appropriate open-source tools to deliver product features through research, proof of concept (POC), and interaction with various open-source forums.
11. Deploy and monitor products on Cloud platforms.
12. Promote and support company policies, procedures, mission, values, and standards of ethics and integrity.

Requirements and Skills:

Competencies:

• Bachelor’s degree with 0-2 years of relevant experience.
• Ability to analyze complex problems and translate them into data science algorithms.
• Proficiency in various areas of core ML, including Forecasting, Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, and Deep Learning Algorithms.
• Experience in statistical learning, including Predictive & Prescriptive Analytics, Web Analytics, Parametric and Non-parametric models, Regression, Time Series, Dynamic/Causal Model, Statistical Learning, and Guided Decisions, among others.
• Proficiency in Python and/or R.
• Experience with big data analytics, identifying trends, patterns, and outliers in large volumes of data.
• Strong experience with big data platforms like Hadoop (Hive, Pig, Map Reduce, HQL, Scala).
• Experience with Teradata, SQL, relational databases, and data warehousing.

Additional Preferred Qualifications:

• Domain knowledge of one or more divisions in Retail.
• Published papers or given talks in leading academic and research journals.
• Published papers or given talks in Data Science Forums.
• Hold data science-related patents.
• Experience with data warehouse platforms like NoSQL Databases (Cassandra).
• Experience with GPU/CUDA for computational efficiency.