Data Scientist
@ Gap Inc.

India
On Site
Full Time
Posted 3 days ago

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XXXXXXXXX XXXXXXXXXXXXX XXXXXXXX****** @gap.com
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Job Details

About the Role

In the Data Scientist role at Gap Inc., you are responsible for designing, developing, and programming systems to consolidate and analyze diverse unstructured big data sources. Your work will generate actionable insights and solutions for various business units in collaboration with GapTech, PDM & Business.

What You'll Do

You will develop software programs, algorithms and automated processes that cleanse, integrate and evaluate large datasets from multiple sources. You will:

  • Manipulate large amounts of data across diverse subjects.
  • Collaborate with data scientists and engineers to prepare data pipelines.
  • Build, validate, and maintain AI/ML and deep learning models.
  • Diagnose, optimize performance and develop statistical models.
  • Present actionable insights to stakeholders.
  • Participate in cross-functional projects and assignments.

Who You Are

You possess advanced proficiency in R, Python, Spark, Hive, and SQL in both on-premises and Azure cloud environments. You have hands-on experience with ML techniques and classical predictive methods (e.g., logistic regression, decision trees, ANN/CNN, boosted trees, SVM, TensorFlow). You can communicate complex ideas in simple terms and work effectively in cross-functional teams.

Company Commitment

At Gap Inc., we stand for equality, inclusivity, and sustainability. Our global team is dedicated to making a positive impact, ensuring accountability, and driving real change every day.

Key skills/competency

Data Scientist, Big Data, Machine Learning, Python, R, SQL, Spark, Hive, Azure, Deep Learning

How to Get Hired at Gap Inc.

🎯 Tips for Getting Hired

  • Research Gap Inc.'s culture: Understand its mission, values, and sustainability commitment.
  • Tailor your resume: Emphasize data science and ML projects.
  • Showcase technical skills: Highlight proficiency in Python, R, Spark, and SQL.
  • Prepare case studies: Demonstrate big data analysis and ML model success.

📝 Interview Preparation Advice

Technical Preparation

Review Python and R libraries.
Practice SQL queries for big data.
Study Spark and Hive basics.
Work on ML model case studies.

Behavioral Questions

Prepare STAR examples.
Discuss teamwork scenarios.
Explain conflict resolution.
Demonstrate adaptability examples.

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