Job
Description
Pyramid overview 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, youll be challenged to harness Targets impressive data breadth to build the algorithms that power solutions our partners in in Marketing, Supply Chain Optimization, Network Security and Personalization rely on About The role As Senior Engineer, you will join a Target Tech team responsible for Promotion forecasting and optimization. You will play crucial role in designing, implementing, and optimizing the machine learning solutions in production. Additionally, youll apply best practices in software design, participate in code reviews, create a maintainable well-tested codebase with relevant documentation. At an organizational level, you will conduct training sessions, present work to technical and non-technical peers/leaders, 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 MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience 4 plus years of experience in end-to-end application development, data exploration, data pipelining, API design, optimization of model latency Expertise in MLOps frameworks and hands on experience in MLOps tools preferably Google Vertex ai 2 plus years of experience deploying Machine Learning algorithms into production environments - including model and system monitoring and troubleshooting Highly proficient programming in Scala and/ or Python/ Pyspark Good understanding of Big Data tech - specifically Hadoop, Kafka, Spark Experience in handling streaming data and real-time forecasting solutions deployment Solid understanding of data analysis techniques, including data cleaning, preprocessing, and visualization Demonstrated ability collaborating with data scientists, software engineers and product managers to understand the business requirements and translate to machine learning solutions at scale Excellent communication skills with the ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives Self-driven and results oriented - able to meet tight timelines Motivated, team player with ability to collaborate effectively across global team Understanding of retail industry and pricing concepts is added advantage Bonus Points: Extensive experience with Deep Learning frameworks TensorFlow, Pytorch or Keras PhD in Computer Science, Applied Mathematics, Statistics, Physics or related quantitative field Extensive experience developing highly distributed ML systems at scale Familiarity with Vertex AI and Cloud ML ecosystem will be desirable Experience in mentoring the junior team members ML skillset and career development .
