Description: JOIN US AS A SR DATA SCIENTIST - RECOMMENDATIONS 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 prioritize 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 and data scientist behind one of the most loved retail brands, delivering joy to millions of our guests, team members, and communities. Join our global in-house technology team of more than 4,000 engineers, data scientists, architects, coaches and product managers striving to make Target the most convenient, safe and joyful place to shop. We use agile practices and leverage open-source software to adapt and build best-in-class technology for our team members and guests-and we do so with a focus on diversity and inclusion, experimentation and continuous learning.
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 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. About you:
- 4-year degree in quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience
- 3+ years of professional experience or equivalent industry experience
- Experience designing and developing deep learning, machine learning, optimization and statistical models
- Strong hands-on programming skills in Python. Knowledge of SQL, Hadoop/Hive, Spark, and/or Scala
- Good working knowledge of mathematical and statistical concepts, algorithms and computational complexity
- Excellent analytical thinking skills
- Strong problem solving skills; develop creative and 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
- Self-driven and results oriented; able to meet tight timelines
- Strong team player with ability to collaborate effectively across geographies/time zones
Americans with Disabilities Act (ADA)
- MS or PhD in a quantitative field
- Experience with recommender systems
Target will provide reasonable accommodations (such as a qualified sign language interpreter or other personal assistance) with the application process upon your request as required to comply with applicable laws. If you have a disability and require assistance in this application process, please visit your nearest Target store or Distribution Center or reach out to Guest Services at 1-800-440-0680 for additional information.