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Senior, Data Scientist - Machine Learning Engineer - job 3 of 9

Position Summary... What you'll do... At Walmart, we enable the connection between supplier brands and retail shoppers at unprecedented scale. As primary stewards of our brand promise, "Save Money. Live Better," we work alongside some of the most talented people in the world to engage with the more than 150M households who shop with us. This is a unique opportunity to join a high growth business within the largest company in the world. We believe all digital advertising can be targeted and accountable - and we have Walmart's sales data to prove it. Walmart Connect wins when suppliers invest in digital media to drive growth; Walmart and our supplier partners win when your digital expertise helps sell more goods online and offline. Growth in our digital advertising business is key to Walmart's overall growth strategy.About the role:The Customer Digital Identity (CDI) organization is enabling the company to better understand who the Walmart customer is. At the same time, we are ensuring streamlined processes, security, scalability, regulatory compliance and best in class customer experience. The CDI team will amplify customer centricity by deepening the company's understanding of customers and their preferences. When we do that, we can serve them when and how they need . This team will work with other teams within the Walmart Membership (W+), Walmart Connect (WMC) and Data Ventures.The Senior Data Scientist will lead our development efforts on deploying Machine Learning models in production environment, our other research data scientist experiment . This is more an ml production focus role than machine learning experimentation. The ideal c andidate is someone who has good knowledge and background in deployment of machine learning models in production at industrial scale.This exciting opportunity will join a team of data scientists embedded within the business unit to develop tools that quantify the impact of investment and operational decisions on the Customer, Associate and Shareholder.Location:Sunnyvale, CA (preferred), San Bruno, CAYou'll sweep us off our feet if...• Demonstrable background in ML Model Development involving Classical ML and Deep Learning in various do main .• Deep expertise in Machine Learning Development Cycle- development, deployment and Monitoring• Strong background of using Model Experimentation ( MLFlow ), Data Versioning (DVC), maintaining CI/CD pipelines via Jenkins, Github A ctions and orchestration pipeline tools (Airflow, Prefe ct ) . Similar tools as above is ok.• You are skilled in Python. Scala is optional.• You are experienced with modeling, optimization, statistical modeling, Ridge/ Lasso and elastic net regression. Familiar with ML frameworks: Scikit learn, TensorFlow, PyTorch .• You are experienced in ETL practices and basic data engineering . SQL experience is required , working experience in SparkSQL or PySpark is needed.• You have experience with cloud environments including Azure, Google Cloud, etc.• Solid MLOps practices including good design documentation, unit testing, integration testing and source code control (git).• Interest in building capabilities in LLMOps especially around LLM depl o yment tooling and Evaluation.• You are experienced with agile methodologies using project planning and tracking management tools e.g., JIRA• You're naturally curious on how things work and excited by solving challenges at the scale of a Fortune 1 Retailer.You'll make an impact by...• Support the development of the Customer Decision & Segmentation Engine. Pr ovide M L Engineer capabilities to cover the entire customer shopping journey.• Identify data collection opportunities to better understand the customer/associate experience. Support the build out of data feature store.• Help put models into production and mentor other data scientist in doing so.Qualifications:• Masters degree in Computer Science, Information Technology or related field• 5+ years MLOps , Machine Learning in Production experience• PhD preferred in Computer Science, Information Technology or related fieldAt Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more.You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable.For information about PTO, see https://one.walmart.com/notices .Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart.Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.For information about benefits and eligibility, see One.Walmart .The annual salary range for this position is $117,000.00-$234,000.00Additional compensation includes annual or quarterly performance bonuses.Additional compensation for certain positions may also include:- StockMinimum Qualifications...Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.Option 1- Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years' experience in an analytics related field. Option 2- Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years' experience in an analytics related field. Option 3 - 5 years' experience in an analytics or related field.Preferred Qualifications...Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture.Primary Location...640 W California Avenue, Sunnyvale, CA 94086-4828, United States of America
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What You Should Know About Senior, Data Scientist - Machine Learning Engineer, Walmart

Joining Walmart as a Senior Data Scientist - Machine Learning Engineer means diving into the world of innovative digital solutions that drive our commitment to 'Save Money. Live Better.' In this role, you'll be part of the Customer Digital Identity (CDI) organization, focusing on deepening our understanding of customers while ensuring top-notch security and regulatory compliance. You’ll take charge of deploying machine learning models that make a real impact on customers’ shopping experiences. Working closely with an inspiring team of data scientists, you will leverage advanced tools and techniques to not only quantify the effects of operational decisions but also enhance customer engagement. Your expertise in machine learning development cycles, MLOps practices, and predictive analytics will be pivotal. If you have a knack for deploying machine learning models at scale, a strong foundation in Python, cloud environments like Azure or Google Cloud, and an adventurous spirit for problem-solving, we want to meet you! With locations in Sunnyvale and San Bruno, you'll enjoy a collaborative workspace that fosters innovation. Plus, you'll benefit from competitive pay, comprehensive health coverage, and professional development opportunities like Live Better U. If you're ready to make an impact in a dynamic environment within the world’s largest retailer, this is the opportunity for you!

Frequently Asked Questions (FAQs) for Senior, Data Scientist - Machine Learning Engineer Role at Walmart
What are the responsibilities of a Senior Data Scientist - Machine Learning Engineer at Walmart?

As a Senior Data Scientist - Machine Learning Engineer at Walmart, you will lead the deployment of machine learning models in a production environment, ensuring they operate on an industrial scale. You'll work on the Customer Decision & Segmentation Engine, identify data collection opportunities, and mentor other data scientists. Your role will also involve collaborating with teams within the Walmart Membership and Data Ventures to facilitate a better customer experience while maintaining best practices in MLOps.

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What qualifications do I need for the Senior Data Scientist - Machine Learning Engineer role at Walmart?

To qualify for the Senior Data Scientist - Machine Learning Engineer position at Walmart, you should hold a master’s degree in Computer Science, Information Technology, or a related field, complemented by at least 5 years of experience in MLOps and machine learning in production. A Ph.D. is preferred. Additionally, strong expertise in Python, SQL, ETL practices, and various machine learning frameworks like Scikit Learn and TensorFlow is essential for success in this role.

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What skills are essential for a successful Senior Data Scientist - Machine Learning Engineer at Walmart?

Essential skills for a Senior Data Scientist - Machine Learning Engineer at Walmart include proficiency in Python, experience in deploying machine learning models, strong knowledge of classical ML and deep learning techniques, and familiarity with MLOps practices. Hands-on experience with cloud environments, data engineering, and tools like Jenkins and Airflow is also vital. A natural curiosity and problem-solving mindset will help you thrive in this fast-paced environment.

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How does the Senior Data Scientist role contribute to Walmart's overall growth strategy?

The Senior Data Scientist role is critical to Walmart's overall growth strategy by amplifying customer understanding and enhancing engagement through data-driven insights. By deploying advanced machine learning models, the Senior Data Scientist will help shape the company's approach to digital advertising, enabling suppliers to effectively reach customers and thereby drive sales growth online and offline.

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What can I expect from the work environment at Walmart as a Senior Data Scientist - Machine Learning Engineer?

At Walmart, you can expect a collaborative and innovative work environment as a Senior Data Scientist - Machine Learning Engineer. You'll have the opportunity to work with some of the best minds in the industry while utilizing cutting-edge technology to solve real business challenges. The culture promotes curiosity, continuous learning, and supports professional development through programs like Live Better U.

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Common Interview Questions for Senior, Data Scientist - Machine Learning Engineer
Can you describe your experience with deploying machine learning models in production?

In response, highlight specific projects where you've successfully deployed machine learning models, emphasizing the tools and techniques used, such as CI/CD pipelines and cloud environments. Discuss challenges faced during deployment and how you overcame them while ensuring the models operated effectively in real-life scenarios.

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What is your familiarity with MLOps practices?

Detail your understanding of MLOps, including the entire lifecycle of machine learning applications from development to deployment and monitoring. Mention any specific tools you've used, such as MLFlow or DVC, and share experiences that demonstrate your capability in maintaining pipelines and operationalizing machine learning.

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How do you approach machine learning model experimentation?

Discuss your systematic approach to model experimentation, including your methods for testing various algorithms, using cross-validation techniques, and employing ML frameworks like TensorFlow or PyTorch. Share an example of a successful experiment and its impact on your project's outcomes.

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What techniques do you use for feature engineering?

Explain your process for identifying and creating features that enhance model performance. Include examples of techniques you employ, such as statistical methods or domain-specific approaches, and how these contribute to understanding customer behavior.

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Can you discuss your experience with cloud computing platforms?

Outline your experience working with cloud platforms like Google Cloud or Azure, mentioning specific tools and services you've utilized for deploying and managing machine learning solutions. Highlight any scalability or performance improvements achieved through cloud implementation.

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What are your favorite machine learning tools and frameworks?

Share your top machine learning tools, such as Scikit Learn, TensorFlow, or PyTorch. Explain why you prefer them based on ease of use, performance, or specific project requirements. This gives insight into your technical proficiency and preferences.

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How do you ensure the security and compliance of customer data?

Discuss the measures you take to secure data, including encryption, access control, and compliance with relevant regulations. Convey your understanding of key privacy laws and how you incorporate them into the data science process, ensuring customer trust.

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What strategies do you use for continuous learning and self-improvement in data science?

Mention resources you rely on, such as online courses, webinars, or community forums, to stay current with advancements in data science and machine learning. Focus on your proactive approach to learning new techniques and technologies that enhance your expertise.

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How do you measure the success of your machine learning models?

Elucidate your criteria for measuring model performance, such as accuracy, precision, recall, or F1 score. Discuss how you validate models before deployment and the importance of maintaining monitoring systems to track model performance post-launch.

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What is your experience with statistical modeling methods?

Share your background in statistical modeling techniques, including regression models like Ridge, Lasso, and Elastic Net. Provide examples of how these methods have contributed to solving specific business problems or bolstering model accuracy in your past work.

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November 30, 2024

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