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Hybrid Data Scientist - Predictive Analytics for Customers

Allianz

Guildford

Hybrid

GBP 50,000

Full time

3 days ago
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Job summary

A leading insurance firm based in Guildford is seeking a Data Scientist. You will collaborate with cross-functional teams to solve business challenges through data experimentation and predictive modeling. The ideal candidate has strong experience in statistical analysis, machine learning, and data visualisation. This role offers around £50,000 per year along with flexible benefits. Hybrid working is supported, allowing you to balance work and personal commitments effectively.

Benefits

Flexible buy/sell holiday options
Annual performance-related bonus
Contributory pension scheme
Development days
Discounts on insurance products
Volunteering days

Qualifications

  • Proven experience as a Data Scientist with analytical models development.
  • Proficiency in Python, R, and SQL for data manipulation.
  • Solid understanding of statistical analysis and hypothesis testing.

Responsibilities

  • Collaborate with stakeholders to develop data-driven solutions.
  • Analyse complex datasets to identify patterns and trends.
  • Develop advanced machine learning models for predictive analytics.
  • Create visualisations to communicate insights effectively.
  • Document methodologies and results for reproducibility.

Skills

Statistical analysis
Machine learning
Data visualisation
Programming languages (Python, R, SQL)
Problem-solving skills
Excellent communication

Tools

AzureML
TensorFlow
Keras
PyTorch
PowerBI
Job description
A leading insurance firm based in Guildford is seeking a Data Scientist. You will collaborate with cross-functional teams to solve business challenges through data experimentation and predictive modeling. The ideal candidate has strong experience in statistical analysis, machine learning, and data visualisation. This role offers around £50,000 per year along with flexible benefits. Hybrid working is supported, allowing you to balance work and personal commitments effectively.
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