Sr Applied Data Scientist - Personalization (applied ML, PyTorch, RecSys)

Target•Brooklyn Park, NC

6d•Hybrid

About The Position

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 at scale to automate and optimize decisions at scale. Whether you join our Applied 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 Digital Marketing, Supply Chain Optimization, Advanced AI, Search and Personalization/RecSys rely on. As a Sr Data Scientist, you’ll work on the Target Data Science Recommendations team collaborating with 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 perform data exploration and analysis, implement algorithmic solutions given specifications, push solutions to our production environment, and analyze performance and trade-offs. 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 and strategic goals and leverage this knowledge while building requirements and solutions for each business need.

Requirements

MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research or relevant work experience
3 plus years of experience developing machine learning models using deep learning frameworks such as PyTorch or JAX
Experience building recommendation, personalization, search, ranking or retrieval systems at scale
Strong programming skills in Python and SQL
Demonstrated experience with optimization, statistics, probability and experimental design
Experience evaluating models through offline analysis on large-scale datasets and online experimentation, including statistical analysis and interpretation of results
Knowledge of large-scale data processing and analytics platforms such as Spark
Extensive experience leveraging generative AI tools to accelerate development, experimentation and model delivery
Ability to communicate complex technical concepts and results to both technical and non-technical audiences
Demonstrated ability to translate business problems into scalable data science solutions
Self-driven, results-oriented and able to meet tight deadlines
Motivated team player who thrives in a collaborative - global environment

Responsibilities

Perform data exploration and analysis
Implement algorithmic solutions given specifications
Push solutions to our production environment
Analyze performance and trade-offs
Understand Agile principles
Follow best-practice software design
Participate in code reviews
Create a maintainable and well-tested codebase with relevant documentation
Document and present work to technical and non-technical peers
Build knowledge on business priorities and strategic goals
Leverage this knowledge while building requirements and solutions for each business need