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Data Science Manager

Posted 13 days ago by Redimeer

£100,000 - £110,000 Annual
Permanent
Not Specified
I.T. & Communications Jobs
London, United Kingdom
Job Description

My client is the leading data and analytics platform for specialty and commercial insurance globally. They are working on revolutionising the insurance industry by simplifying and streamlining insurance operations with cutting-edge technology.

They are seeking an experienced and highly skilled Data Science Manager to lead their team of Data Scientists. In this role, you will be responsible for overseeing the end-to-end Data Science and Machine Learning Modelling processes, including data ingestion, feature creation and selection, cross validation, hyperparameter tuning and model assessment to model deployment, to support the teams in solving complex business problems for their clients in the commercial insurance, brokerage, and reinsurance industries.

Responsibilities

Team Leadership:

  • Lead and mentor the Data Science team, ensuring they follow best practices, adhere to quality standards, and deliver consistent and timely results
  • Develop and implement robust data science and modelling architectures, pipelines, and processes to build linear and nonlinear models efficiently and effectively
  • Foster a culture of innovation, encouraging the team to explore and adopt new technologies and methodologies to stay ahead of industry trends
  • Manage the data science project lifecycle, including planning, execution, monitoring, and delivery
  • Lead by example when it comes to the company's leadership principles or Data Science/ML expertise
  • Develop and report on key KPIs within Data Science that drive the success of the business

Stakeholder Collaboration:

  • Collaborate with the Product and Commercial leaders to develop compelling offerings that drive revenue and customer benefits
  • Work closely with the Engineering team to make sure that output of Data Science teamwork can be injected into product offerings
  • Be comfortable in front of customers and instil confidence with your ability to understand customer needs and convey complex concepts in a simple manner
  • Engage with key stakeholders, including executives, to communicate Data Science strategy, progress, and results
  • Be an authoritative voice within the business to represent the needs of the market and the value that the products can offer

Technical Skills and Qualifications

  • Machine Learning Expertise: Deep understanding of machine learning algorithms, principles, and their application
  • Insurance Risk Modelling Expertise: Deep understanding of insurance risk models, actuarial science, and the ability to apply statistical and machine learning techniques to assess and predict risk in the insurance domain
  • Insurance Domain Expertise: In-depth understanding of the insurance sector. Ability to leverage this expertise to drive data-driven decision-making and to develop models that reflect the nuances of insurance risk and customer behavior
  • Strong data wrangling and processing skills along with a background in analysis and predictive modelling
  • Extensive experience with supervised classification and regression modelling using linear and nonlinear techniques
  • Knowledge of the full end-to-end modelling lifecycle from feature creation, selection, model-building, hyperparameter optimisation and model assessment
  • Experience and familiarity with the tools and tech stack being used by team such as Python, Apache Spark (preferably with PySpark) and Python pandas, numpy, scikit-learn, Supervised Learning (Regression, Classification), Unsupervised (Clustering), Dimensionality Reduction, Model Selection and Optimisation, Feature Selection, Metric Selection, Bootstrapping, Ensembling & Stacking Methods
  • Exposure with various GEN AI models (LLMs) would be an added advantage

Benefits include:

  • Tax efficient Pension Scheme with 5% matched contribution
  • Private medical insurance from Vitality Healthcare
  • Life insurance AIG Life
  • Learning & Development fund for all employees
  • 25 days annual leave (plus public holidays)

The company offers hybrid working with the office near Liverpool Street, London

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