Data Scientist

Aquent; United Kingdom; On-site; GBP 40,000 - 65,000; Full time

Job summary

Aquent seeks a Data Scientist to join their Paid Experiences team. This role involves leveraging quantitative analysis and data mining to enhance advertising strategies across various platforms. Candidates should have a strong academic background and proficiency in Python, R, and statistical methods. Join us in shaping innovative solutions that improve user experiences while ensuring platform integrity.

Qualifications

• Master's degree required in a relevant field.
• Experience in quantitative analysis and data mining on complex data sets.
• Knowledge in machine learning techniques and A/B testing.

Responsibilities

• Collect, analyze, and interpret statistical data.
• Collaborate with product and engineering teams to identify trends and solutions.
• Perform data analyses to drive decision-making.

Skills

Data analysis

Quantitative analysis

Data mining

Machine learning

Statistics

Education

Master’s degree in Computer Science, Engineering, Information Systems, Analytics, Mathematics, Economics, Physics, Applied Sciences, or a related field.

Tools

Python

R

SAS

Matlab

Job description

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Data Scientist (Analytics) is to help teams make better data-driven decisions. This is done in the following way:

• Collect, organize, interpret, and summarize statistical data in order to contribute to the design and development of 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
• Quantitative analysis techniques, including clustering, regression, pattern recognition, or descriptive and inferential statistics.

THE ROLE

We have 3 areas in Experiences: Organic (focusing on consumers), Paid (focusing on business/advertisers), Platform (infra to help scale the other two)

• We are looking for a Data Scientist to join our Paid Experiences team.
• Specifically, this will work with our Engineers, Designers and Product Managers to:
• Understand what integrity experiences prevent advertisers from running ads successfully
• Help advertisers (self-)remediate to unblock their campaigns, while protecting the organisation from harm

WHO WE ARE LOOKING FOR

• Excited about giving millions of users a day a more supportive integrity experience when they face enforcements or encounter harm on the platform
• Excited about optimising systems for scale at the intersection of user facing experiences and platform capabilities
• Enjoys thinking through how we best form partnerships with other teams and how scalable solutions should be governed effectively.
• Enjoys getting their hands dirty to understand data and system disconnects and can drive insightful root-cause-analysis

Minimum Qualifications

• Requires a Master’s degree in Computer Science, Engineering, Information Systems, Analytics, Mathematics, Economics, Physics, Applied Sciences, or a related field.
• Requires knowledge or experience in the following: Performing quantitative analysis including data mining on highly complex data sets.
• Scripting language: Python
• 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
• Machine learning techniques
• Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics