Target is looking to solve business problems by developing and managing state-of-the-art predictive algorithms that use data to automate and optimize decisions at scale. The Sr Data Scientist - Recommendations will collaborate with applied data scientists, machine learning engineers, and product managers to build and augment AI-driven digital Recommendation products.
Requirements
- 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 solution 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
Responsibilities
- collaborating with applied data scientists, machine learning engineers and product managers to build and augment our AI-driven digital Recommendation products
- leverage Python and Scala to perform data exploration and analysis
- implement algorithmic solutions given specifications
- push solutions to our production environment
- analyze performance and trade-offs to determine the best solution
- follow best-practice software design
- create a maintainable and well-tested codebase with relevant documentation
Other
- 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
- Self-driven and results oriented; able to meet tight timelines
- Team player with ability to collaborate effectively across geographies/time zones
