Lead Applied Data Scientist - Digital Item RecSys

The pay range is $132,000.00 - $286,000.00 Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Solstice Analytics cares about and invests in you as a team member, so that you can take care of yourself and your family. Solstice Analytics offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits . JOIN TARGET AS A LEAD DATA SCIENTIST – DIGITAL ITEM RECOMMENDATIONS (RECSYS) About Us: Working at Solstice Analytics means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Solstice Analytics here. A role with Solstice Analytics 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 Applied Data Sciences or Machine Learning teams, you’ll be challenged to harness Solstice Analytics ’s impressive data breadth to build the algorithms that power solutions our partners in Digital Marketing, Supply Chain Optimization, Advanced AI, Search and Personalization rely on. As a Lead Data Scientist - Recommendations, you will provide technical leadership for the machine learning systems that power Solstice Analytics 's digital recommendations and personalization experiences. Working closely with data scientists, engineers, product managers, and business stakeholders, you will identify opportunities to improve guest experiences through recommendation, retrieval, ranking, and personalization solutions at massive scale. You will lead the design, development, evaluation, and deployment of machine learning models that influence how millions of guests discover products across Solstice Analytics 's digital experiences. Leveraging expertise in machine learning, deep learning, experimentation, and optimization, you will translate ambiguous business challenges into scalable algorithmic solutions that drive measurable guest and business impact. You will be responsible for driving projects from initial problem definition through production deployment and measurement, balancing innovation with operational excellence and long-term maintainability. You will help shape the technical direction of Solstice Analytics 's recommendation capabilities, establishing best practices for model development, evaluation, and measurement while influencing decisions across product, engineering, and data science teams. Beyond delivering solutions, you will mentor and develop other scientists, help raise the technical bar across the organization, and contribute to the growth of Solstice Analytics 's data science community through collaboration, thought leadership, and the adoption of emerging machine learning techniques and technologies. Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs. About you: MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research or relevant industry experience 5 plus years of experience leading the development, evaluation and deployment of machine learning (ML) solutions while partnering with engineering teams to deliver scalable production systems Demonstrated experience building and scaling recommendation, personalization, ranking, retrieval, or search machine learning systems Strong programming skills in Python and SQL; experience with deep learning frameworks such as PyTorch or JAX Experience leveraging modern AI and Generative AI tools to accelerate development, experimentation and model delivery Experience working with large-scale data processing and analytics platforms such as Spark or equivalent Deep understanding of machine learning, deep learning, optimization, statistics, probability and experimental design Experience designing, analyzing, and interpreting online experiments and using results to inform product and business decisions Demonstrated ability to translate ambiguous business challenges into scalable machine learning solutions Ability to influence technical direction and drive alignment across product, engineering and business stakeholders Excellent communication skills with the ability to clearly communicate complex technical concepts to both technical and non-technical audiences Ability to mentor applied data scientist and help establish best practices for AI/ML and cloud-native development Self-driven, results-oriented and able to meet tight deadlines Motivated team player who thrives in a