Staff Data Scientist

Walmart Canada

$225K — $286K *
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Master's degree or equivalent in relevant fields plus 2 years of experience; or Bachelor's degree plus 4 years of experience
  • Proficiency in Python, SQL, Unix Shell, Git, NumPy, Pandas, and Matplotlib
  • Experience with big-data tools like Spark/PySpark for processing and feature extraction
  • Familiarity with Computer Vision techniques, including pretrained models and embeddings
  • Proven background in deep learning frameworks such as PyTorch or TensorFlow

Responsibilities

  • Design and develop large-scale personalization and computer-vision systems
  • Implement and support data pipelines, collaborating with engineering for model integration
  • Contribute to ML/DL roadmap for personalization and lead product lifecycle phases
  • Analyze pre/post-deployment metrics and recommend tuning adjustments
  • Develop generative-modeling workflows for image/text asset creation

Benefits

  • Comprehensive health benefits including medical, vision, and dental coverage
  • 401(k) plan and stock purchase options
  • Company-paid life insurance
  • Generous paid time off policy including parental and family care leaves
  • 100% company-paid education assistance for college degrees
Full Job Description
What you'll do...

Position: Staff Data Scientist

Number of Positions Available: Seven (7)

Job Location: 1375 Crossman Avenue, Sunnyvale, CA 94089

Duties: Design, develop, and productionize large-scale personalization and computer-vision systems (candidate generation, ranking, visual similarity, image-based recommendations). Design, implement, and support deployment of large-scale data pipelines; collaborate with engineering to integrate models into serving systems. Contribute to discovery and formulation of the ML/DL roadmap for personalization and lead selected phases of the product lifecycle in partnership with Product and Engineering. Collaborate on online-inference deployments, analyze pre/post-deployment metrics, and recommend performance/tuning changes. Adapt pretrained vision and multimodal models via transfer learning for retrieval, ranking, and relevance; manage embeddings/feature stores. Develop generative-modeling workflows for automated image/text asset creation (e.g., diffusion/GAN/VAE-style or equivalent) with quality/brand checks and measured impact. Contribute input to metric definitions and experiment design; collaborate on A/B and offline relevance evaluation; present readouts with recommendations. Contribute to architecture and road-mapping via design discussions and documentation; contribute to invention disclosures/patents.

Minimum education and experience required: Master's degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (any), or related field and 2 years of experience in an analytics related field; OR Bachelor's degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (any), or related field and 4 years of experience in an analytics related field.

Skills required: Experience with coding in Python, SQL, Unix Shell, Git, NumPy, Pandas, and Matplotlib. Experience with big-data tools Spark/PySpark and Scalding for large-scale processing and feature pipelines. Experience with Computer Vision for working with existing images (segmentation/detection, visual similarity) and applying pretrained vision models/embeddings. Experience implementing deep learning models in a modern framework (PyTorch, TensorFlow). Experience with CNN-based image embeddings and multimodal (vision-language) models. Experience applying pretrained models and transfer-learning techniques. Experience with text embeddings and language models, including TF-IDF, Word2Vec, Doc2Vec, and RNN/LSTM. Experience with machine-learning algorithms including classification and clustering (support vector machines) and dimensionality reduction (PCA). Experience with recommender systems, including matrix factorization and collaborative filtering, and embedding-based retrieval and ranking. Experience programming computer algorithms. Experience contributing to statistical inference and hypothesis testing, including familiarity with offline relevance metrics (Recall[redacted], NDCG) and A/B methodology, and presenting experiment readouts. Experience contributing to production Machine Learning (ML) systems, including batch/stream processing and integration with serving/online-inference systems in partnership with engineering. Experience validating deployments and analyzing runtime performance. Experience with generative modeling and foundation-model adaptation (GANs, VAEs, diffusion) and evaluating generated outputs. Employer will accept any amount of graduate coursework, graduate research experience or professional experience with the required skills.

Salary Range: $225,077/year to $286,000/year. Additional compensation includes annual or quarterly performance incentives.

Benefits: At Walmart, we offer competitive pay as well as performance-based incentive 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, education assistance with 100% company paid college degrees, company discounts, military service pay, adoption expense reimbursement, and more.

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.com.

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