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As a Principal Data Scientist for Walmart Global Tech, you'll have the opportunity to
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Drive data-derived insights across a wide range of retail divisions by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives
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Direct the gathering of data, assess data validity and synthesize data into large analytics datasets to support project goals
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Utilize big data analytics and advanced data science techniques to identify trends, patterns, and discrepancies in data. Determine additional data needed to support insights
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Build and train AI/ML models for replication for future projects
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Deploy and maintain the data science solutions
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Communicate recommendations to business partners and influence future plans based on insights
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Consult with business stakeholders regarding algorithm-based recommendations and be a thought-leader to develop these into business actions.
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Closely partners with the Senior Manager & Director of Data Science to drive data science adoption in the domain
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Guides. data scientists, senior data scientists & staff data scientists across multiple sub-domains to ensure on-time delivery of ML products
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Drive efficiency across the domain in terms of DS and ML best practices, ML Ops practices, resource utilization, reusability and multi-tenancy.
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Lead multiple complex ML products and guide senior tech leads in the domain in efficiently leading their products.
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Drive synergies across different products in terms of algorithmic innovation and sharing of best practices.
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Proactive identification of complex business problems that can be solved using advanced ML, finding opportunities and gaps in the current business domain
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Evaluates proposed business cases for projects and initiatives
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Translates business requirements into strategies, initiatives, and projects and aligns them to business strategy and objectives, and drives the execution of deliverables
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Sets relevant deliverables based on the established success criteria and define key metrics to measure progress and effectiveness of the solution
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Quantifies business impact and ensures regular impact measurement of all ML products in the domain.
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Identifies and reviews model evaluation metrics based on analytical requirements
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Ensures testing information is documented and maintained by the team
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Play a key role to solve complex problems, pivotal to Walmarts business and drive actionable insights
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Utilize product mindset to build, scale and deploy holistic data science products after successful prototyping
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Demonstrate incremental solution approach with agile and flexible ability to overcome practical problems
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Articulate and present recommendations to business partners and influence plans based on insights
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Partner and engage with associates in other regions for delivering the best services to customers around the globe
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Work with the customer-centric mindset to deliver high-quality business-driven analytic solutions.
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Drive innovation in approach, method, practices, process, outcome, delivery, or any component of end-to-end problem solving
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Proactively engages in the external community to build Walmarts brand and learn more about industry practices
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Promote and support company policies, procedures, mission, values, and standards of ethics and integrity
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Masters with > 12 years OR Ph.D. with > 10 years of relevant experience. Educational qualifications should be Computer Science/Statistics/Mathematics or a related area.
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Minimum 5 years of experience as a data science technical lead
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Ability to lead multiple data science projects end to end.
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Deep experience in building data science solution in areas like fraud prevention, forecasting, shrink and waste reduction, inventory management, recommendation, assortment and price optimization
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Deep experience in simultaneously leading multiple data science initiatives end to end - from translating business needs to analytical asks, leading the process of building solutions and the eventual act of deployment and maintenance of them Strong experience in machine learning: Classification models, regression models, NLP, Forecasting, Unsupervised models, Optimization, Graph ML, Causal inference, Causal ML, Statistical Learning, experimentation & Gen-AI
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In Gen-AI, it is desirable to have experience in embedding generation from training materials, storage and retrieval from Vector Databases, set-up and provisioning of managed LLM gateways, development of Retrieval augmented generation based LLM agents, model selection, iterative prompt engineering and finetuning based on accuracy and user-feedback, monitoring and governance.
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Ability to scale and deploy data science solutions.
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Strong Experience with one or more of Python and R.
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Experience in GCP/Azure
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Strong Experience in Python, PySpark
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Google Cloud platform, Vertex AI, Kubeflow, model deployment
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Strong Experience with big data platforms - Hadoop (Hive, Map Reduce, HQL, Scala)
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Experience with GPU/CUDA for computational efficiency
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years experience in an analytics related field.
Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years experience in an analytics related field.
Option 3: 7 years experience in an analytics or related field.