JOIN TARGET AS A SENIOR DATA SCIENTIST – SEARCH (NLP and APPLIED ML)
About Us:
As a Fortune 50 company with more than 350,000 team members worldwide, Target is an iconic brand and one of America's leading retailers.
Working at Target means the opportunity to help all families discover the joy of everyday life. Caring for our communities is woven into who we are, and we invest in the places we collectively live, work and play. We prioritise relationships, fuel, and develop talent by creating growth opportunities, and succeed as one Target team. At our core, our purpose is ingrained in who we are, what we value, and how we work. It’s how we care, grow, and win together.
Every time a guest enters a Target store or browses Target.com, they experience the impact of Target’s investments in technology and innovation. We’re the technologists behind one of the most loved retail brands, delivering joy to millions of our guests, team members, and communities.
This role is with Target’s Search team which uses AI to power search on target.com and App. The Search team builds the core relevance engine and products that power Target’s digital experience. As a Sr Data Scientist on this product – you’ll work with business partners to provide solutions for business problems in a fast-paced and global environment. You’ll have the opportunity to design quality, flexible and performant AI systems and services at scale. You’ll also architect AI solutions that capture, process and mine huge datasets in the retail industry. We’ll also promote innovative thinking as well as the opportunity to utilize advanced machine learning algorithms and NLP techniques to improve our Mobile and Web Search systems at Target!
Key Responsibilities:
Develop and deploy scalable deep learning models to improve the search experience of Target guests
Architect and implement large-scale AI systems using test-driven development practices
Build NLP technology for query and document analysis, processing, and understanding
Create data pipelines for feature/label extraction and generation
Conduct data analysis to identify opportunities and improve models
Conduct research to advance the state-of-the-art machine learning and NLP technologies
Mentor and partner with other engineers to develop software that meets business needs
Follow agile methodology for software development and technical documentation
Innovate constantly and keep systems up to date with current technologies
Requirements:
MS in Computer Science, Electrical Engineering, Mathematics, Statistics, or related quantitative field
Overall, 4+ years of ML experience, 1+ year of experience in deploying machine learning algorithms into production environments.
Research or industry experiences in relevant fields such as Information Retrieval, ML, NLP, or Recommendation/Recommender systems
Good understanding of Search indexing, Retrieval and Ranking
Proficient in Python or Java with advanced coding and problem-solving skills
Extensive experience in implementing and integrating ML models in production with high traffic
Experience querying large databases with SQL, HQL or some variations
Excellent interpersonal and communication skills to work with global teams
Constant learner mentality that stays on the leading edge of Search/Ranking, ML and NLP advancements
Preferred:
PhD/MS in Computer Science, Mathematics, Statistics, Physics, or related quantitative field
Proven track record of achieving significant engineering (applied ML) or academic research
Experience with Solr at scale
eCommerce experience
Why grow your career with Target’s Data Science?
You will work directly on the AI/ML problems that have the most impact on Target's entire digital, supply chain, forecasting, merchandising teams.
We value diversity. We believe that diversity and inclusion is of core importance when we try to create positive in-store experiences for our guests, and we think it is also critically important when building our teams. Read more about our commitment to diversity and inclusion
We love open source! Many of our team members contribute to open-source communities and get to do it during work time. We try to contribute back to our communities where we can and are grateful to be able to open source some of our own projects!
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