Job Description
As a Staff Data Scientists for Walmart Labs, 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 plans.
- 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
Your Responsibility:
- 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.
What You Will Bring
- PhD with > 4 years of experience / Master's degree with > 7 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 analyzing 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: Forecasting, Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms and Re-inforecement 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 Modeling
- Experience working with big data - identifying trends, patterns, and outliers in large volumes of data.
- Experience with Python and one Object Oriented Programming Language.
- Worked with at least one main stream 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 : Merchandising Divisions in Retail.