Data Scientist

Trust In Soda

Posted a day ago, valid for 17 days

London, Greater London EC1R 0WX

Full Time

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Sonic Summary

The job position is for a Data Scientist with a start date of ASAP and a duration of 12 months, offered as a remote role.
Candidates are required to have 10-15 years of experience in experimentation for user-facing products and proficiency in data querying languages such as SQL.
The salary rate ranges from £400 to £550 per day, with a focus on applied statistics and experimentation like A/B testing in an industry setting.
The responsibilities include collaborating with engineering, product management, and design teams to improve appeal mechanisms for account enforcements.
Ideal candidates should have experience working with major technology companies and be skilled in statistical or mathematical software such as R, SAS, or MATLAB.

Data Scientist – HIRING ASAPStart date: ASAPDuration: 12 MonthsLocation: RemoteRate: £400 - £550 per day PAYESkills:

10-15 years’ experience
Experimentation for user facing products.
Narrative excellence
Data querying language: SQL
Statistical or mathematical software including one of the following: R, SAS, or MATLAB
Applied statistics or experimentation, such as A/B testing, in an industry setting.
Ability to write queries.
Experience working on an app or a website, for Big Technology businesses like Netflix, Amazon, Spotify, etc.

Responsibilities:

Work with the engineering teams, product managers, design teams, etc.
We have several teams within Transparency & Appeal and specifically looking for someone to cover Appeals for account enforcements, i.e. when we take an action on a user or advertiser’s account.
This is our highest priority area, and we are looking for a seasoned data scientist to support us both strategically and operationally.
You will work with our Engineers, Designers and Product Managers to:
Improve the mechanisms that exist to appeal (e.g. Consider account disables, feature limits and lightweight enforcement's
Performing quantitative analysis including data mining on highly complex data sets
Data querying languages, such as SQL, scripting languages, such as Python, or statistical or mathematical software, such as R, SAS, or MATLAB
Applied statistics or experimentation, such as A/B testing, in an industry setting.

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