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Data Scientist

Taylor Root
Job LocationLondon
EducationNot Mentioned
Salary£50,000 - £65,000 per annum
IndustryNot Mentioned
Functional AreaNot Mentioned
Job TypePermanent , full-time

Job Description

Responsibilities

  • Develop predictive models and analytic solutions, with moderate supervision, to support underwriting, pricing, and marketing functions within the Company.
  • Collaborate in brainstorming potential data sources for predictive variables, identifying, acquiring, evaluating, and documenting data from internal and external sources.
  • Extract and manipulate data using data management tools from various sources, understanding and combining data to create analytics datasets.
  • Analyze data, draw meaningful conclusions, and contribute to developing solutions to enhance profitability and/or growth.
  • Introduce innovative methodologies, algorithms, tools, and technologies to address assigned problems.
  • Communicate findings to business partners, ensuring successful integration of projects into business processes.
  • Participate in developing solutions to implement models into production, collaborating with IT in model design and testing.
  • Support business requests requiring statistical analysis and collaborate with other analytics teams to achieve objectives.
  • Build partnerships with key counterparts and monitor the performance and usage of models, ensuring reports meet audience needs.
Qualifications
  • Minimum of a bachelors degree, preferably in Statistics, Mathematics, Analytics, or Computer Science. Advanced degree in Statistics or Predictive Analytics is strongly preferred.
  • 3+ years of predictive analytics experience, preferably in the Insurance industry or Financial Services.
  • Proficiency in Python, including developing complex functions and classes within an automated framework.
  • Data engineering skills, including visualization (histogram, heat map, interaction plots), data cleaning, and SQLDW schema creation.
  • Modeling expertise in XG Boost, logistic regression, linear regression (severity and frequency modeling), model scoring, and interpretation.
  • Automation skills, building functions and sklearn pipelines, comfortable with yaml files for configuring inputs.
  • Familiarity with tools such as Databricks, VS Code, Github, and SQL server.
  • Intermediate knowledge in statistical analysis and multivariate procedures; knowledge of Machine Learning techniques and AI is a plus.
  • Experience with a statistical package (Python, R), data management (SQL), and/or programming is required; experience with Databricks is a plus.
  • Experience with text analytics is a plus.
Proficient in Microsoft Suite applicationsPlease note our advertisements use PQE/salary levels purely as a guide. However we are happy to consider applications from all candidates who are able to demonstrate the skills necessary to fulfil the role.Please note that your personal information will be treated in accordance with our Privacy Policy.

Keyskills :
Machine LearningPythonData Science

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