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Senior Data Scientist

Vermelo RPO
Posted 21 hours ago, valid for 16 days
Location

Manchester, Greater Manchester M17 1DJ, England

Salary

£22,000 - £26,400 per annum

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Contract type

Full Time

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Sonic Summary

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  • Markerstudy Group is seeking a Senior Data Scientist for a hybrid role based in Manchester or Haywards Heath.
  • The position requires a minimum of 5 years of experience in data science and a relevant advanced degree.
  • The successful candidate will lead the development of predictive models and collaborate with various teams to enhance business processes.
  • Key skills include proficiency in programming languages such as Python and R, as well as a strong understanding of machine learning techniques.
  • The salary for this role is competitive and commensurate with experience.

Job Title: Senior Data Scientist

Location: Manchester or Haywards Heath (hybrid working)

Role Overview

Markerstudy Group are looking for a Senior Data Scientist to join a quickly growing company in developing ambitious solutions across a range of insurance lines, by leveraging vast data assets and state-of-the-art processing capabilities.

Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. The majority of business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.

As a Senior Data Scientist, you will use your advanced analytical skills to:

  • Lead the development of cutting-edge, bespoke machine learning predictive models, including risk classification, claims behaviour and fraud
  • Identify and create data solutions that create value
  • Work collaboratively with the pricing, claims handling and fraud teams to provide insight across the business
  • Your ideas and solutions will enable improvements to products, prices and processes giving Markerstudy a critical advantage in the increasingly competitive insurance market.

Your ideas and solutions will enable improvements to products, prices and processes giving Markerstudy a critical advantage in the increasingly competitive insurance market.

Identify and create solutions that leverage vast data assets and state-of-the-art processing capabilities to improve company performance and our customer-centric offerings. This will be across Motor, Home and Commercial Lines businesses.

Key Responsibilities:

  • Be the technical lead in the development of predictive models that solve business challenges through one-off analyses or bespoke modelling. Such work would include:
  • Risk classification, such as area or vehicle classification
  • Development of models for new products or specialised risks, such as pet insurance
  • Testing of innovative predictive modelling techniques, such as automated interaction detection or the automatic smoothing of linear model trends using GAMs
  • The development and maintenance of predictive models for application and claims fraud, and claims handling processes
  • Be involved in the development and testing of state-of-the-art hyper-parameter tuning methods and drive efficiency in the tuning of standard machine learning processes.
  • Work collaboratively with the data and pricing teams to identify solutions to wider modelling challenges
  • Use a wide range of data science and statistical techniques
  • Adapt known machine learning techniques to create solutions/models that are state-of-the-art and go beyond business requirements
  • Research and leverage new and existing internal and/or external data sources
  • Communicate results to key decision makers across the business
  • Assist in the deployment and monitoring effort to ensure efficient productisation of the solutions created

Key Skills and Experience:

  • D. or masters in statistics, data science or equivalent field
  • Minimum of 5 years’ experience within data science
  • Experience and detailed technical knowledge of GLMs /Elastic Nets, GBMs, GAMs, Random Forests, and clustering techniques
  • Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL)
  • Proficient at communicating results in a concise manner both verbally and written

Behaviours:

  • Motivated by technical excellence
  • Team player
  • Self-motivated with a drive to learn and develop
  • Logical thinker with a professional and positive attitude
  • Passion to innovate and improve processes
  • Personality and a sense of humour

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