Applied Data Scientist - Search Ranking

Target•Brooklyn Park, MN

1d•Hybrid

About The Position

Working at Target means helping all families discover the joy of everyday life. 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 Statistics, Optimization 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 Optimization, Network Security 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. Through your understanding of the foundations and working principles of machine learning algorithms, linear algebra, probability theory, statistics, and optimization theory, you will perform data exploration and analysis (look at distributions, find anomalies, create simple visualizations, etc.) and implement algorithmic solution given specifications, while adhering to best practices in model development. We will look to you to understand and actively follow foundational programming principles (best practices, know about unit tests, code organization, basics of CI/CD etc.) and create a well-maintainable & tested codebase with relevant documentation. You will get the opportunity to develop in one or more approved programming languages (Java, Scala, Python, R), and learn and adhere to best practices in data analysis and data understanding. As you follow agile processes, you will implement prototypes for individual components of software or data science solutions and understand and leverage basic data structures and algorithms in implementing solutions. Leverage your high-level understanding in business domain to gain knowledge of high-level Target business priorities, strategic goals and their impact, as well as details of the specific business sub-problem you are focused on. You will collaborate with peers on their product and document and present work to peers and participate in code reviews and gain broader understanding of different components within the application. The exciting part of retail? It’s always changing! Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

Requirements

4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience
Exceptional Python programming experience with advanced technical problem-solving skills
1 plus year of experience implementing end to end ML models and algorithms into production
Knowledge of search indexing, ranking, information retrieval, query understanding or recommendation / recommender systems
Experience deploying Machine Learning algorithms into production environments
Experience with ML Ops (VetexAI, Bigquery, etc.) and various testing frameworks and containerization (Docker, Kubernetes, etc.)
Experience querying large databases with SQL, HQL or some variations
Excellent interpersonal and communication skills that can partner with a global teams
Constant learner mentality that stays on the leading edge of search, ranking, applied ML, LLM’s and NLP advancements

Responsibilities

Influence by interacting within the Data Sciences team
Perform within the scale and scope of your role by implementing solutions
Contribute to Data Sciences’ and Target’s culture by modeling the culture
Perform data exploration and analysis (look at distributions, find anomalies, create simple visualizations, etc.)
Implement algorithmic solution given specifications, while adhering to best practices in model development
Understand and actively follow foundational programming principles (best practices, know about unit tests, code organization, basics of CI/CD etc.)
Create a well-maintainable & tested codebase with relevant documentation
Develop in one or more approved programming languages (Java, Scala, Python, R)
Learn and adhere to best practices in data analysis and data understanding
Implement prototypes for individual components of software or data science solutions
Understand and leverage basic data structures and algorithms in implementing solutions
Gain knowledge of high-level Target business priorities, strategic goals and their impact, as well as details of the specific business sub-problem you are focused on
Collaborate with peers on their product
Document and present work to peers
Participate in code reviews
Gain broader understanding of different components within the application