Product Data Scientist
@ Google

Hyderabad, Telangana, India
$150,000
On Site
Full Time
Posted 9 hours ago

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About the Product Data Scientist Role

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding, and a strategic perspective to partners across the organization. As a data-loving member of the team, you will weave stories with meaningful insights from data and make critical recommendations for fellow Googlers in Engineering and Product Management.

You will partner with teams across the company to apply Google's best Data Science techniques to its biggest enterprise opportunities and work closely with Research, Core Enterprise ML and ML Infrastructure teams to build scalable solutions.

Minimum Qualifications

  • Bachelor's degree in a quantitative field.
  • 5 years of work experience in analysis applications and coding (Python, R, SQL) or 2 years plus a Master's degree.

Preferred Qualifications

  • Master's degree in a related quantitative field.
  • 5 years of experience with analysis applications and coding skills.
  • Experience with deep learning models and debugging AI issues.
  • Experience with large-scale data transformation pipelines for batch ML inference.

Responsibilities

  • Define and report Key Performance Indicators and launch impact with leadership.
  • Collaborate with PM, UX, and Engineering for metric-backed OKRs.
  • Develop hypotheses to enhance AI product performance using advanced techniques.
  • Design, prototype, and implement unsupervised and supervised ML models.
  • Evolve simulation strategies to improve experimental reliability.

Key skills/competency

  • Data Analysis
  • Machine Learning
  • Python
  • Statistical Analysis
  • Deep Learning
  • SQL
  • Data Transformation
  • Model Prototyping
  • Experimentation
  • Cross-functional Collaboration
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How to Get Hired at Google

🎯 Tips for Getting Hired

  • Customize your resume: Highlight relevant data science and ML skills.
  • Showcase quantitative projects: Detail statistical analysis and coding expertise.
  • Leverage networking: Connect with current Google employees on LinkedIn.
  • Prepare for technical interviews: Practice ML case studies and coding challenges.

📝 Interview Preparation Advice

Technical Preparation

Review Python, R, SQL coding challenges.
Study deep learning model implementation.
Practice ML model prototyping exercises.
Brush up on large-scale data transformations.

Behavioral Questions

Describe a time you solved complex problems.
Explain how you manage cross-team communications.
Detail a challenging project and your role.
Discuss handling tight deadlines under pressure.

Frequently Asked Questions