Details:
Requirements:
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You have expertise in exploratory data analysis and visualisation (e.g. with SQL, Python/Pandas, R, or similar).
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You love using data to answer high-level questions about how people use a product.
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You have 3+ years of experience.
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You have experience in e-commerce.
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You are interested in beauty products.
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You’re self-sufficient but work well in a team.
It would be a bonus if:
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You have experience with recommendations algorithms, MongoDB, A/B testing.
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You can communicate technical ideas, analyses and results clearly.
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You have worked in a startup or to deadlines.
Benefits:
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Work remotely from any location with flexible hours.
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Opportunity to grow with the company and be offered a permanent role.
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Work in one of the hottest BeautyTech startups, getting hands-on experience and learning more about the beauty industry.
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Really make an impact instead of making coffees and photocopies - see your ideas come to life without layers of hierarchy.
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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.