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Data Scientist V

Posted 02 February 2025
Salary £425 - £500 per day, Benefits: Negotiable
LocationLondon
Job type Contract
Discipline Data
ReferenceBH-113236
Contact NameNathan Peters

Job description

Data Scientist – HIRING ASAP

Start date: ASAP
Duration: 10 Months
Location: Remote
Rate: £425 - £500 per day PAYE.
Interview Process: 2 stages.
 
Skills:
  • 10-15 years’ experience
  • Experimentations 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.
  • Requires a master’s degree in computer science, Engineering, Information Systems, Analytics, Mathematics, Economics, Physics, Applied Sciences, or a related field.
  • Performing quantitative analysis including data mining on highly complex data sets.
  • Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics.
  • Enjoys getting their hands dirty to understand data and system disconnects and can drive insightful root-cause-analysis.
  • Passionate about building solid and scalable measurement solutions.
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 enforcements)
  • Identify how we meet the needs and expectations of our users and what opportunities there are to improve.
  • Balance reducing harm on the platform with protecting voice and revenue, alongside regulation and cost guardrails.
  • Align the business on your improvement ideas and support their implementation.
  • You will also work closely with data partners to establish or improve our measurement capabilities in this space, ensuring that the team always stays on target.
  • Collect, organize, interpret, and summarize statistical data to contribute to the design and development of our clients’ products.
  • Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products.
  • Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
  • Inform, influence, support, and execute our product decisions and product launches.
  • May be assigned projects in various areas including, but not limited to, product operations, exploratory analysis, product influence, and data infrastructure.
  • Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors.
  • Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
  • Perform data analyses on tactical (feature-level) and strategic (team objectives and goals) work to drive team direction.
  • Develop strategic narrative based on analytical insights and priorities.
  • Think about key questions and metrics to define success for any product/feature.
  • In connection with these duties, may apply knowledge of the following: 
  • 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.
  • Communicating the results of analyses to product or leadership teams to influence strategy.
  • Machine learning techniques
  • ETL (Extract, Transform, Load) processes.
  • Relational databases
  • Large-scale data processing infrastructures using distributed systems.
  • Quantitative analysis techniques, including clustering, regression, pattern recognition, or descriptive and inferential statistics.
Bonus Skills:
  • Python/R