Data Scientist
@ Gap Inc.

India
On Site
Full Time
Posted 3 days ago

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XXXXXXXXXX XXXXXXXXX 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 in partnership with GapTech, PDM & Business.

What You'll Do

  • Develop software programs, algorithms and automated processes to clean, integrate and evaluate large data sets.
  • Manipulate large amounts of data from diverse subject areas and collaborate on data pipelines.
  • Build, validate, and maintain ML/Deep Learning models and statistical analyses.
  • Communicate actionable insights from big data to various stakeholders.
  • Participate in diverse projects and assignments with cross-functional teams.

Who You Are

  • Proficient in R, Python, Spark, Hive, and common scripting languages.
  • Advanced SQL skills for large datasets in both on-prem and Azure cloud environments.
  • Experience with ML, predictive techniques (e.g., logistic regression, decision trees, SVM, Tensorflow) and data visualization.
  • Adept at both detailed analysis and high-level insight communication.
  • Proven ability to collaborate and influence product and analytics roadmaps.

Key skills/competency

  • Data Analysis
  • Machine Learning
  • Python
  • SQL
  • Big Data
  • R
  • Spark
  • Hive
  • Azure
  • Statistical Modeling

How to Get Hired at Gap Inc.

🎯 Tips for Getting Hired

  • Research Gap Inc.'s culture: Study their mission, values, and recent news.
  • Customize your resume: Highlight big data and ML expertise.
  • Prepare technical examples: Showcase projects involving Python and SQL.
  • Practice interview questions: Focus on data analytics and collaboration skills.

📝 Interview Preparation Advice

Technical Preparation

Review Python libraries and ML frameworks.
Practice SQL queries on large datasets.
Study cloud environment (Azure) deployment setups.
Revisit algorithm optimization techniques.

Behavioral Questions

Describe a team project challenge.
Explain handling tight deadlines under pressure.
Share examples of cross-team collaborations.
Discuss decision-making in ambiguous situations.

Frequently Asked Questions