Principal Data Scientist Advanced Machine Learning

About Us

As a Fortune 50 company with more than 400000 team members worldwide Target is an iconic brand and one of Americas leading retailers.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 andyoullbuild relationships by being authentic and respectful.

Overview about TII

At Target we have a timeless purpose and a proven strategy. And thathasnthappened by accident. Some of the best minds fromdifferent backgroundscome together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especiallyapparentin Bengaluru where Target in Indiaoperatesas a fully integrated part of Targets global team and has more than 4000 team members supporting the companys global strategy and operations.

Team Overview

Our Generative AI team oversees the development of Target specific use cases which are of strategic importance toTarget.Wealso support various teams within Target so that they will be able to build productsas per Target standardsregardinguse of responsible AI.

Position Overview

As a Principal Data Scientist at Target you will get an opportunity to design developdeployandmaintaindata sciencemodels and tools.Youllwork closely with applied data scientists dataanalystsandbusiness partners to continuously learn and understand evolving business needs.Youllalso collaborate with AI/ML engineers and data scientists on peer teams to build andproductionize groundbreaking GenAI based solutions for various teams.

In this role as a Principal Data Scientist you will:

Analyse large datasets for insights leading to business process improvements orsolution development.

Contribute to the research design and implementation of leading-edge generative AItechnologies to address and solve complex problems that contribute to finding

solutions for the retail world.

Work with Multimodal LLMs enhance model performance fine-tune LLMs

Work with the team to build andmaintaincomplex software systems and tools.

Adopt modular architecture and good software development/engineering practices toenhance the overall product performance and guide other team members.

Produce clean efficient code based on specifications.

Coordinate the analysis troubleshooting and resolution of issues in the models andsoftware.

About You

Bachelors/MS/PhD in Mathematics Statistics Computer Science or other relatedfields.

10 years of relevant experience.

Strong analytical thinking. Ability to creatively solve business problems innovating

innovative approaches where.

Ability to clean transform manipulate and analyse large datasets for insights leading

to business process improvements or solution development.

Experience in developing testing andmaintaininglarge codebases in a collaborative

environment while meeting industry best practices.

Highly proficient in programming skills in Python SQL Hadoop/Hive.

Exposure to programmatic use of GenAI/LLMs and related ecosystem.

Experience in developing Deep Learning based solutions usingPyTorchor TensorFlow

Self-driven and results oriented. Willing to stretch to meet tight timelines.

Strong teamplayer with ability to collaborate effectively across geographies/ timezones.

Excellent written and verbal communication skills.

Preferred Qualifications:

Knowledge of containerized solutions using Docker/ Kubernetes.

Exposure to Prompt Engineering Embedding Generation Retrieval Augmented

Generation(RAG) space (e.g. Vector DB Elastic Search) will be plus.

Knowledge of Computer Vision & Deep Learning Methods.

Good working Knowledge of Mathematical and statistical concepts optimization datastructures and algorithms data analysis visualizations and applications of same in avariety of business problems.

Experience deploying solutions with large-scale business impact in commercialsettings.

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