Data Scientist

Morgan McKinley
1 year ago
Applications closed

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Data Scientist - Measurement Specialist

Exciting opportunity to work with a Big4 Tech Company as a Data Scientist, remote in the UK!


Data Scientist

Location: Remote in the UK

Contract Duration: 10 months

Responsibilities:

- 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


Skills:

o Performing quantitative analysis including data mining on highly complex data sets

o Data querying languages, such as SQL, scripting languages, such as Python, or statistical or mathematical software, such as R, SAS, or Matlab

o Applied statistics or experimentation, such as A/B testing, in an industry setting

o Communicating the results of analyses to product or leadership teams to influence strategy

o Machine learning techniques

o ETL (Extract, Transform, Load) processes

o Relational databases

o Large-scale data processing infrastructures using distributed systems

o Quantitative analysis techniques, including clustering, regression, pattern recognition, or descriptive and inferential statistics

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