Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.
A role with Target Data Science & Engineering 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.
Apply best practices in software design and participate in code reviews.
Build and maintain a well-tested, well-documented codebase.
Lead training sessions and present work to technical and non-technical audiences.
Develop a strong understanding of business priorities and strategic goals, and leverage this knowledge when crafting solutions.
Bachelor’s degree in a quantitative field (STEM) or equivalent experience
6+ years of experience in end-to-end application development, data exploration, data pipelining, API design, and model latency optimization
2+ years of experience deploying machine learning models to production, including monitoring and troubleshooting
Proficiency in Java, Scala, and/or Python
Strong understanding of Big Data technologies, including Hadoop, Kafka, and Spark
Solid foundation in data analysis: cleaning, preprocessing, and visualization
Proven ability to collaborate with data scientists, software engineers, and product managers to deliver scalable ML solutions
Excellent communication skills with an ability to tell data-driven stories through visualizations and narratives
Self-driven, results-oriented, and able to meet tight deadlines
Motivated team player who thrives in a collaborative global environment
Good To have Skills:
Extensive experience with Deep Learning frameworks (TensorFlow, PyTorch, Keras)
Expertise in developing highly distributed machine learning systems at scale
Familiarity with Google Cloud’s Vertex AI and the broader Cloud ML ecosystem
Experience mentoring junior team members in ML skills and career development