Data Scientist- Content Creation

**About Us**

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.

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, and you'll build relationships by being authentic and respectful.

**Overview about TII**

At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different 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.

**Pyramid**O**verview**

**Team Overview**

The Content Creation team within Data Sciences will help build AI solutions leveraging GenAI, computer vision and traditional ML models for various marketing or site content use-cases. The team will play a crucial role in helping Target drive relevancy with guests.

**P**os**ition Overvie**w**

As a Data Scientist, you’ll influence by interacting with the Data Sciences team, Product teams, Scientist/Engineer individual contributors from other pillars, and business partners.
- You will perform within the scale and scope of your role by defining solutions and beginning to identify problems to solve and contribute to Data Sciences’ and Target’s culture by modeling and contributing to the culture.
- You’ll get the opportunity to use your expertise in one or more of the following areas: machine learning, probability theory & statistics, optimization theory, Simulation, Econometrics, Deep Learning, Natural Language processing or computer vision.
- We will look to you to learn the design and work on the implementation of an algorithmic solution (e.g., recommendation or forecasting algorithm), including data understanding, feature engineering, model development, validation and testing, and deployment to a production environment.
- You’ll drive development of problem statements that capture the business considerations, define metrics/measurement to validate model performance, and drive feasibility study with data requirements and potential solutions approaches to be considered.
- You’ll evaluate tradeoffs of simple vs complex models/solutions in determining the right technique to employ for a business problem and develop and maintain a nuanced understanding of the data generated by the business, including fundamental limitations of the data.
- You’ll leverage your proficiency in one or more approved programming languages (Java, Scala, Python, R), and ensure foundational programming principles in developing code (best practices, writes unit tests, code organization, basics of CI/CD etc.) are followed in developing the team’s products/models.

Core responsibilities of this job are described 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)
- Around 1-2 years of relevant industry experience
- Solid foundations in math and programming
- Strong fundamentals in Probability, Statistics, Linear Algebra
- Knowledge and experience developing optimization, simulation and statistical models
- Experience in working with image, text data, embeddings, building vision models and Gen AI tools is a bonus
- Experience in Machine Learning frameworks such as TensorFlow, PyTorch or similar libraries
- Hands-on programming skills in Python, SQL, Hadoop/Hive
- Good problem-solving skills combined with strong analytical abilities
- Good communication skills. Ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives

**Know More About Us here**:

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Life at Target**:

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