62969 – Data Scientist

Career Moves; London; On-site; GBP 50,000 - 80,000; Full time

Job summary

A leading company is seeking a seasoned Data Scientist to enhance user experience and improve platform mechanisms for account enforcement appeals. The role requires a Master's degree and proficiency in data mining, quantitative analysis, and collaboration with cross-functional teams for effective product improvements. This is a strategic position focused on balancing user support with operational efficiency.

Qualifications

• Master's degree in a relevant field required.
• Experience with data mining on complex data sets.
• Knowledge of quantitative analysis techniques.

Responsibilities

• Collect, analyze, and summarize statistical data.
• Collaborate with Product and Engineering teams.
• Develop strategic narratives from data insights.

Skills

Quantitative analysis

Data mining

Statistical analysis

Root-cause analysis

Collaboration

Education

Master’s degree in Computer Science or related field

Tools

SQL

Python

R

SAS

Matlab

Job description

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Overview of the role
• Our client is looking for someone to cover Appeals for account enforcements, when we take an action on a user or advertiser’s account
• They are looking for a seasoned data scientist to support both strategically and operationally
• You will work with Engineers, Designers and Product Managers to: Improve the mechanisms that exist to appeal ( Consider account disables, feature limits and lightweight enforcements) and 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.

Responsibilities of the role
• Collect, organize, interpret, and summarize statistical data in order to contribute to the design and development of client 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

Skills & Attributes
• Excited about giving millions of users a day a more supportive integrity experience when they face client enforcements
• Excited about optimising systems for scale at the intersection of user facing experiences and platform capabilities while balancing multiple competing priorities
• 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
• Passionate about building solid and scalable measurement solutions

Qualifications & Experience
• 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
• Data querying language: SQL
• 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
• Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics