The Data Science & Analytics organizations mission is to increase our speed frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering product analytics causal inference economics statistical modeling and machine learning. Aligned and partnering with product verticals we use this extensive toolbelt to discover new opportunities and unmet use cases influence and shape the product roadmap and prioritization build data products and measure impact on our community of players and developers.
This is a temporary part-time position requiring no more than 20 hours per weekfor a 3-month duration with possibility to extend.
Teams Hiring for this role:
- Foundation AI:Our AI evaluation team focuses on generating high-quality models and consistently improving our evaluation models.
- Safety:Managing account relationships and the real-time morphing of linguistic mapping.
- Economy:Drive creator success and growth by exploring marketplace structure and pricing.
You Will:
- Collaborate with data scientists and engineers to research and develop advanced data analytics causal inference experiment design and machine learning solutions to power the business and product innovations.
- Conduct in-depth research to address complex data-related challenges.
- Work on projects that have a real impact on our products services and business strategy.
- Apply your work to expedite product innovations including in-experience experiments friend recommendations and dynamic resource allocation for experience servers
- Present your findings and recommendations to both technical and non-technical stakeholders.
You Have:
- Possessing or pursuing a PhD degree in a quantitative field such as Statistics Applied Math Computer Science Economics or Computational Social Science Operations Research Computer Engineering Electrical Engineering.
- At least 1 year of experience doing causal inference or machine learning or experiment design via research or prior internship.
- Proficiency in one or more programming languages (e.g. SQL Python or R)
- Proficiency in big data query/processing languages and tools such as SQL Hive Spark or Airflow.
- Passion for applying scientific rigor to advance dynamic consumer products.
- Experience in developing production solutions is a plus.
- Experience with ML modeling
You may redact age date of birth and dates of attendance/graduation from your resume if you prefer.
Required Experience:
Intern
The Data Science & Analytics organizations mission is to increase our speed frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering product analytics causal infere...
The Data Science & Analytics organizations mission is to increase our speed frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering product analytics causal inference economics statistical modeling and machine learning. Aligned and partnering with product verticals we use this extensive toolbelt to discover new opportunities and unmet use cases influence and shape the product roadmap and prioritization build data products and measure impact on our community of players and developers.
This is a temporary part-time position requiring no more than 20 hours per weekfor a 3-month duration with possibility to extend.
Teams Hiring for this role:
- Foundation AI:Our AI evaluation team focuses on generating high-quality models and consistently improving our evaluation models.
- Safety:Managing account relationships and the real-time morphing of linguistic mapping.
- Economy:Drive creator success and growth by exploring marketplace structure and pricing.
You Will:
- Collaborate with data scientists and engineers to research and develop advanced data analytics causal inference experiment design and machine learning solutions to power the business and product innovations.
- Conduct in-depth research to address complex data-related challenges.
- Work on projects that have a real impact on our products services and business strategy.
- Apply your work to expedite product innovations including in-experience experiments friend recommendations and dynamic resource allocation for experience servers
- Present your findings and recommendations to both technical and non-technical stakeholders.
You Have:
- Possessing or pursuing a PhD degree in a quantitative field such as Statistics Applied Math Computer Science Economics or Computational Social Science Operations Research Computer Engineering Electrical Engineering.
- At least 1 year of experience doing causal inference or machine learning or experiment design via research or prior internship.
- Proficiency in one or more programming languages (e.g. SQL Python or R)
- Proficiency in big data query/processing languages and tools such as SQL Hive Spark or Airflow.
- Passion for applying scientific rigor to advance dynamic consumer products.
- Experience in developing production solutions is a plus.
- Experience with ML modeling
You may redact age date of birth and dates of attendance/graduation from your resume if you prefer.
Required Experience:
Intern
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