ImpactAs a Senior Data Scientist working remotely on the Personalization Machine Learning Team, you will collaborate closely with diverse teams, including product managers, engineers, and fellow data scientists to develop and architect multi-stage ranking systems, develop advanced recommender models and build candidate generation recommenders as well as multi-stage ranking employing multi-label and multi-objective rank optimization techniques. You will work alongside a Principal Data Scientist and Senior Machine Learning Engineer where you will be responsible for guiding, planning, and executing the Personalization ML Roadmap to elevate the Shipt.


While no day will look the same, you will be responsible for implementing state of the art Recommendation Algorithms in production, pre-launch experiment design, post-launch measurement, result evaluation, and collaboration with product and analytics teams to define or modify KPIs. You will lead the ideation, design, experimentation, and deployment of cutting-edge machine learning solutions on the Shipt ML Platform, working in tandem with your ML team and engineering partners. You will also partake in weekly stand ups and actively participate in code and design reviews within the team. Given the dynamic nature of the Recommendation field, particularly with recent advancements in NLP and LLM, staying relevant and sharing knowledge with other team members is a key responsibility.

What You’ll Need to Be Successful

PhD or MS in Computer Science, Machine Learning, Mathematics, or a related field.

5+ years of experience in Machine Learning.

3 years of experience in large scale recommendation systems using both traditional and modern recommendation algorithms (i.e Factorization to Deep Learning)

Experience in building Multi-Arm Bandit and Reinforcement Learning driven Recommender Systems.

Industry experience in multi-stage, multi-objective ranking, machine-learning-based information retrieval, learning-to-rank, Deep Learning, fine-tuning LLM.

Strong knowledge of ML-Frameworks (e.g., Pytorch, Vowpal Wabbit, scikit-learn).

Deep expertise in NLU/NLP and awareness of the latest trends in Large Language Models and Deep Learning and its usage in building Recommender Systems.

Proficiency in Python, git, and airflow.

Deployment of models to production via fast-api and /or GRPC.

Work Arrangement:

Shipt considers candidates located near a Shipt office or workspace in Birmingham, San Francisco, or Minneapolis to be hybrid, which means that they have the flexibility to work from home (with leader approval) or at a Shipt office in order to facilitate the ability to innovate, collaborate, and spark team connections. In-office expectations will vary by role and leader.  Certain roles may require in-office presence on a full-time basis. Please work with your recruiter to learn more about the classification of this role.

About Shipt

Shipt is a retail tech company that connects people to reliable, high-quality delivery with a personal touch. Shipt connects customers to the things they want from the stores they love, retail businesses to more satisfied customers, and workers to new earning opportunities.

At Shipt, we aim to put our team first to boost a sense of belonging, spark opportunities for growth, provide unique benefits and commit to giving back to our communities in ways that make life better, both personally and professionally. We understand that our service, our culture, and our connection to our communities are only made better by every single person who shows up to work here every day.  Learn More.

Shipt is an independently operated, wholly owned subsidiary of Target Corporation and available in more than 5,000 U.S. cities. Shipt was founded and is headquartered in Birmingham, Alabama. For more information, please visit Shipt’s company site at Shipt.com.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or any other characteristic protected by law.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Metro Areas of Boston, District of Columbia, Los Angeles, San Francisco, Seattle and New York City: 

$121,487-$242,974