Data Scientist
@ Gap Inc.

India
On Site
Full Time
Posted 4 days ago

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XXXXXXXXX XXXXXXXXXXX XXXXXXX****** @gapinc.com
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Job Details

About the Role

In this role, you are responsible for the design, development, programming methods, processes and systems to consolidate and analyze unstructured, diverse "big data" sources to generate actionable insights and solutions for businesses across the company. You will support the team to build the Data and Analytics capabilities, enriching the analytical platform on behalf of the entire organization in partnership with GapTech, PDM & Business.

What You'll Do

  • Develop software programs, algorithms and automated processes that cleanse, integrate and evaluate large datasets.
  • Manipulate large amounts of data from diverse subject areas and prepare data pipelines.
  • Build, validate, and maintain AI/ML and deep learning models.
  • Develop statistical models for ad hoc business focused analysis.
  • Communicate actionable insights and complex concepts simply to stakeholders.
  • Participate in projects of diverse scope.

Who You Are

  • Advanced proficiency in R, Python, Spark, Hive and related scripting languages.
  • Expert in using SQL across on-prem and cloud distributed computing environments.
  • Experienced with ML techniques including logistic regression, decision trees, CNN, SVM and Tensorflow.
  • Capable of detailed analysis and summarizing findings for business recommendations.
  • Strong collaboration skills with cross functional teams to influence roadmap.
  • Creative, logical problem solver with proven relationship building skills.

Key skills/competency

  • Data Science
  • Big Data
  • Machine Learning
  • Python
  • R
  • SQL
  • Spark
  • Deep Learning
  • Analytics
  • Statistical Modeling

How to Get Hired at Gap Inc.

🎯 Tips for Getting Hired

  • Research Gap Inc.'s culture: Explore their mission, values, and recent initiatives.
  • Customize your resume: Align skills with data science and analytics experience.
  • Prepare technical examples: Demonstrate proficiency in Python, SQL, and ML techniques.
  • Showcase projects: Highlight real-world data pipeline and modeling projects.

📝 Interview Preparation Advice

Technical Preparation

Review Python and R libraries.
Practice SQL queries on large datasets.
Study ML algorithms and model tuning.
Familiarize with Spark and Hive environments.

Behavioral Questions

Describe a challenging data problem solved.
Explain teamwork in cross-functional projects.
Discuss handling of tight deadlines.
Share examples of clear stakeholder communication.

Frequently Asked Questions