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Senior Applied Data Scientist

Dunnhumby

Gurgaon, Haryana, IndiaOn Site

Original Job Summary

About dunnhumby

dunnhumby is the global leader in Customer Data Science, empowering businesses to compete and thrive in a modern, data-driven economy. We always put the Customer First and work for iconic brands including Tesco, Coca-Cola, and Procter & Gamble.

Our Mission

Our mission is to help businesses grow by championing their customers with big data, AI-driven platforms, and deep market expertise.

Role: Senior Applied Data Scientist

You will apply advanced data science and machine learning techniques to solve complex problems and deliver impactful client solutions. This role involves developing, implementing, and deploying a range of applications while working with a globally diverse and smart team.

What We Expect from You

  • Relevant degree in a related subject
  • Strong programming skills (Hadoop, Spark, SQL, Python)
  • Experience in prototyping and statistical modelling
  • Expertise in analytical techniques, quality assurance, and testing

What You Can Expect from Us

You will enjoy a comprehensive rewards package, flexible working hours, personal flexibility, and thoughtful perks like birthday off. Our investment in cutting-edge technology and our inclusive culture ensure that you have the freedom to experiment and grow.

Flexible Working

We value a good work/life balance with agile working opportunities available. Discuss your flexible needs with your recruiter during the hiring process.

Key skills/competency

  • Machine Learning
  • Data Science
  • Statistical Modelling
  • Hadoop
  • Spark
  • SQL
  • Python
  • Prototyping
  • Quality Assurance
  • Flexible Working

How to Get Hired at Dunnhumby

🎯 Tips for Getting Hired

  • Research dunnhumby's culture: Explore mission, values and recent news.
  • Customize your resume: Highlight data science skills and experience.
  • Emphasize technical expertise: Focus on Hadoop, Spark, Python and SQL.
  • Prepare for interviews: Practice scenario-based technical questions.

📝 Interview Preparation Advice

Technical Preparation

Review Hadoop and Spark documentation.
Practice SQL and Python coding challenges.
Study statistical modeling techniques.
Test prototyping and QA methods.

Behavioral Questions

Describe a challenging data project.
Explain teamwork in global environments.
Discuss time management under pressure.
Share a learning from failure.