About Team:  

Marketplace Data Science team at Walmart Global Tech is focused on using the latest research in artificial intelligence (AI), machine learning (ML), statistics, deep learning, computer vision and optimization to solve business problems in Walmart’s eCommerce. We partner with our product and engineering teams to drive significant measurable business impact. Advanced AI/ML algorithms/models driven by our team help Walmart to optimize experimentation and insights frameworks, business practices, reduce cost and pass those benefits to our customers. The Data Science and ML Engineering community at Walmart Global Tech is active in most of the Hack events, utilizing the petabytes of data at our disposal, to build some of the coolest ideas. All the work we do at Walmart Labs will eventually benefit our operations & our associates, helping Customers Save Money to Live Better. 

What you will do: 

As a Staff Data Scientists for, you’ll have the opportunity to  

• Apply and/or develop ML solutions to develop efficient and scalable models at Walmart scale. 

• Play a key role to solve complex problems, pivotal to Walmart’s business and drive actionable insights from terabytes of data. 

• Leverage data science tools and techniques, keeping abreast with the latest in the community to solve problems for Walmart. 

• Collaborate with counterparts in business, engineering, and science to find impactful solutions to business problems. 

• Define and/or own the model goodness metrics and track the business impact over time. 

• Present recommendations from complex analysis to business partners in clear and actionable form, influencing the future. 

• Develop PoC, present lucidly to the business and evolve the solutions. 

• Take forward the solutions into Pipelines/APIs as needed by the business. 

• Research, learn/disseminate & adapt new technologies to solve problems & improve upon existing solutions. 

• Adopt Wal-Mart’s quality standards and develop and recommend process standards and best practices across the retail industry. 

• Manage the continuous improvement of data science and machine learning by following industry best practices and staying up to date with and extending the state-of-the-art in Machine Learning research. 

• Integrate data science solutions into current business processes. 

• Develop and recommend process standards and best practices in Machine Learning as applicable to the retail industry. 

• Mentor peers and junior members and handle multiple projects at the same time. 

• Peer review and publish work in top tier ML/AI conferences such as NIPS, ICML, AAAI and COLT 

• Participate and speak at various external forums such as research conferences and technical summits. 

• Promote and support company policies, procedures, mission, values, and standards of ethics and integrity. 

What you will bring: 

• PhD with > 6 years of experience / master’s degree with > 8 years of experience / bachelor's degree with > 9 years of experience. Educational qualifications should be preferably in STEM. Experience should be relevant to the role. 

• Experience in analysing complex problems and translating them to data science algorithms with due attention to computational efficiency and testing at scale. 

• Expertise in machine learning, supervised and unsupervised: Time Series Forecasting, latest technique in NLP Deep Learning Algorithms and Reinforcement Learning 

• 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 Modelling 

• Experience working with big data - identifying trends, patterns, and outliers in large volumes of data. 

• Worked with at least one mainstream machine learning framework such as caffe, convNet, Tensor Flow and Torch 

• Experience with SQL, relational databases and data warehouse 

• Experience with big data platforms - Hadoop(Hive, Pig, Map Reduce, HQL) / Spark / H20 

• Domain Knowledge : AdTech and MarTech 

• Experience with multiple stakeholder management, data based story-telling, mentoring peers and juniors, multiple project handling at the same time.