Principal Data Scientist

Posted:
9/29/2024, 5:20:26 PM

Location(s):
Bengaluru, Karnataka, India ⋅ Karnataka, India

Experience Level(s):
Expert or higher

Field(s):
AI & Machine Learning ⋅ Data & Analytics

Principal Data Scientist

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from diverse backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.

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 diverse voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.

As Principal Data Scientist, you will join a Data Sciences team responsible for creating highly personalised offers for our Guests. This team works on both recommendation and optimization.

 You will play crucial role in designing, implementing, and optimising the machine learning solutions in production. We will also expect you to understand best-practice software design, participate in code reviews, create a maintainable and 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. Also, we expect you to guide the ML talent in the team on both algorithms and engineering. 

Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.

Requirements: 

  • 10 + or more years of extensive experience in Machine Learning 
  • Architect performant ML solutions that are built to scale and adopt guiding principles of automation, efficiency and reusability.  
  • Strong experience in one of the general programming languages (Python or Java). Familiarity with Big Data frameworks Like Hadoop and Spark is essential.  Familiarity with Machine learning frameworks like TensorFlow, Pytorch or Keras is preferred.
  • Excellent communication skills. Ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives
  • Drive creation of new standards and best practices with a focus on emerging technologies and author various project related documents and technical roadmaps.  
  • Work in partnership with data scientists, software engineers and product managers to understand the business requirements and translate them to machine learning solutions. 
  • Stay up-to-date with the latest advancements in recommendations and AI research 
  • Self-driven and results oriented; able to meet tight timelines; Team player with ability to collaborate effectively across geographies. 
  • Mentor team members and partners on effective data science modelling and outcomes.  

Preferred: 

  • MS or PhD in a quantitative field 
  • Experience with developing highly distributed ML systems and online recommendation systems.  

Useful Links-

Life at Target- https://india.target.com/

Benefits- https://india.target.com/life-at-target/workplace/benefits

Culture- https://india.target.com/life-at-target/diversity-and-inclusion

Target

Website: https://www.target.com/

Headquarter Location: Minneapolis, Minnesota, United States

Employee Count: 10001+

Year Founded: 1962

IPO Status: Public

Last Funding Type: Post-IPO Equity

Industries: Communities ⋅ E-Commerce ⋅ Retail ⋅ Shopping