Position Summary...

Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales. Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities. Models compliance with company policies and procedures and supports company mission, values, and standards of ethics and integrity by incorporating these into the development and implementation of business plans; using the Open Door Policy; and demonstrating and assisting others with how to apply these in executing business processes and practices.

What you'll do...

About Team: 
Building the right technology foundation for Infrastructure & platforms is vital to success at the scale of Walmart. Our team builds and maintains the foundational technologies that support the tech organization. Included in this are data platforms, enterprise architecture, DevOps, cloud computing, and infrastructure. All of these products and services are supported by scalable and powerful infrastructure, ensuring a secure and seamless employee and customer experience across stores, digital channels, and distribution centers. 

What you'll do:

• Manage end-to-end engineering solutions for Machine Learning at scale.
• Integrate data science solutions into tangible products.
• Write efficient and quality code that can work @ Wal-Mart scale
• Productionize ML models – tackle all model management challenges.
• Parallelize algorithms/model training to make use of distributed infrastructure and reduce training time significantly.
• Adopt Wal-Mart’s quality standards and develop and recommend process standards and best practices across the retail industry.
• Research, learn & adapt new technologies to solve problems & improve existing solutions
• Participate in events to build innovative solutions
• Design, build, test and deploy cutting edge solutions at scale, impacting millions of customers worldwide drive value from data at Walmart Scale
• Interact with data science groups across Walmart to understand their major engineering challenges, build and propose solution for them.
• Identify right open source tools to deliver product features by performing research, POC/Pilot and/or interacting with various open source forums
• Deploy and monitor products on Cloud platforms.
• Promote and support company policies, procedures, mission, values, and standards of ethics and integrity

What you'll bring:

Competencies

• Bachelor's with 0-2 years of relevant experience
• Experience in Analyzing the Complex Problems and translate it into data science algorithms 
• Sound knowledge in several areas in core ML such as Forecasting, Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms.
• Experience in statistical learning: Predictive & Prescriptive Analytics, Web Analytics, Parametric and Non-parametric models, Regression, Time Series, Dynamic/Causal Model, Statistical Learning, Guided Decisions, Topic Modeling 
• Experience with big data analytics - identifying trends, patterns, and outliers in large volumes of data 
• Strong Experience with one or more of Python and R 
• Strong Experience with big data platforms – Hadoop (Hive, Pig, Map Reduce, HQL, Scala) 
• Experience with Teradata, SQL and relational databases, data warehouse

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 – No SQL Databases (Cassandra) 
• Experience with GPU/CUDA for computational efficiency