Data Scientist

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Data Scientist

Beauty Matching Engine

Remote INR 8 - 12 LPA Experience : 3 - 10 YRS. Openings: 1

Details:

Requirements:
  • You have expertise in exploratory data analysis and visualisation (e.g. with SQL, Python/Pandas, R, or similar).

  • You love using data to answer high-level questions about how people use a product.

  • You have 3+ years of experience.

  • You have experience in e-commerce.

  • You are interested in beauty products.

  • You’re self-sufficient but work well in a team.

It would be a bonus if:
  • You have experience with recommendations algorithms, MongoDB, A/B testing.

  • You can communicate technical ideas, analyses and results clearly.

  • You have worked in a startup or to deadlines.

Benefits:
  • Work remotely from any location with flexible hours.

  • Opportunity to grow with the company and be offered a permanent role.

  • Work in one of the hottest BeautyTech startups, getting hands-on experience and learning more about the beauty industry.

  • Really make an impact instead of making coffees and photocopies - see your ideas come to life without layers of hierarchy.

  • A very friendly atmosphere.

 

Min. Qualification:

  • Person with 3+ years of experience in data science. The person should have prior experience with practical data science applications and use cases.
  • Person who loves problem solving through data. She/He should be able to do things hands on by himself or guide a team of data scientists to solve a problem.
  • A person with deep experience in tools like Python / SAS / R and machine learning / predictive modeling techniques/ Machine Learning Algorithms.
  • Strong problem solving and communication skills (English)

Skills Required:

Python, Data Analytics, Data Science, Data Mining

Roles:

  • This is a 3-6 month full-time data scientist contract position with potential to become permanent position based on the performance.
  • Reporting to the Project Manager, focusing on exploratory data analysis and A/B testing for a live beauty product recommendations engine.
  • You’ll explore the rich behaviour data collected as people shop using our recommendations and the results from our A/B tests.
  • You’ll work closely with our technical and product teams to come up with questions and hypotheses about what’s working or could be improved, you’ll help design and interpret future A/B tests, and so you’ll help guide our product roadmap for improving the algorithm.

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