Target-posted 4 months ago
$95,000 - $171,000/Yr
Full-time • Mid Level
Brooklyn Park, MN
General Merchandise Retailers

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. A role with Target Data Sciences means the chance to help develop and manage state of the art predictive algorithms that use data to automate and optimize decisions at scale. Whether you join our Data Sciences or Machine Learning teams, you'll be challenged to harness Target's impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain, Demand Forecasting, Search and Personalization rely on. Every Scientist on Target's Data Sciences team can expect modeling and data science, software/product development of highly performant code for Model Performance to elevate Target's culture, and apply retail domain knowledge. As a Sr Data Scientist, you'll work on the Target Data Science Recommendations team collaborating with applied data scientists, machine learning engineers and product managers to build and augment our AI-driven digital Recommendation products. Through your understanding of deep learning, machine learning, linear algebra, probability theory, statistics, and optimization you'll leverage Python and Scala to perform data exploration and analysis, implement algorithmic solutions given specifications, push solutions to our production environment as well as analyze performance and trade-offs to determine the best solution. We will expect you to understand Agile principles, follow best-practice software design, participate in code reviews, create a maintainable and well-tested codebase with relevant documentation. On the business side, you'll document and present work to technical and non-technical peers, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need. Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.

  • Collaborate with applied data scientists, machine learning engineers, and product managers to build and augment AI-driven digital Recommendation products.
  • Leverage Python and Scala to perform data exploration and analysis.
  • Implement algorithmic solutions given specifications and push solutions to production.
  • Analyze performance and trade-offs to determine the best solution.
  • Understand Agile principles and follow best-practice software design.
  • Participate in code reviews and create a maintainable and well-tested codebase.
  • Document and present work to technical and non-technical peers.
  • Build knowledge on business priorities and strategic goals.
  • 4-year degree in quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience.
  • PhD/MS in Computer Science, Applied Mathematics, Physics, Data Sciences or relevant industry experience.
  • 3+ years end to end experience with applied ML and recommender systems.
  • Experience designing and developing deep learning (PyTorch, TensorFlow), machine learning, optimization and statistical models at scale.
  • Strong hands-on programming skills in Python and extensive experience with SQL, PySpark, Hive, and/or Scala.
  • Experience with ML Ops (Vertex AI, Bigquery, etc.) and various testing frameworks and containerization (Docker, Kubernetes).
  • Good working knowledge of mathematical and statistical concepts, algorithms and computational complexity.
  • Strong problem solving skills; develop innovative solutions to help solve real-world business problems using data sciences approaches.
  • Able to create documents and narrative suggesting actionable insights.
  • Excellent communication skills; able to clearly tell data driven stories through appropriate visualizations, graphs and narratives.
  • Self-driven and results oriented; able to meet tight timelines.
  • Team player with ability to collaborate effectively across geographies/time zones.
  • Comprehensive health benefits including medical, vision, dental, life insurance.
  • 401(k) plan.
  • Employee discount.
  • Short term disability.
  • Long term disability.
  • Paid sick leave.
  • Paid national holidays.
  • Paid vacation.
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