Data Science Manager

Reference

DataSciMan25


Sector

Analysis, Business Analyst, Data & Analytics, Pricing & Data Science


Salary

£80,000 to £100,000 Per Annum


Benefits

Bonus + Excellent Benefits


Town/City

London


Contract Type

Permanent

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A leading global insurance group with a culture rooted in collaboration, expertise and innovation,they aim to promote progress and inspire their clients, employees, investors and communities to achieve their greatest potential. Their work is the catalyst that helps others achieve their goals. In short, they Enable Possibility.

About The Team And The Role

Strategic Analytics is a growing team at that develops innovative predictive models and analytical tools to improve pro?tability and growth as well as providing deep analytical insight for decision makers.

To be successful, we need to develop powerful models, tools and insights that give  a unique, competitive advantage.

As Data Science Manager you will play a crucial role in developing analytics-led solutions to business issues.

You will work closely with senior stakeholders in claims and within the wider strategic analytics team to identify issues and develop actions which are data led to drive enhancements to the business. You will work with and direct other data scientists to build best-in-class predictive models with creativity, statistical rigor and business sense.

Key Tasks And Responsibilities

  • Work closely with business partners to understand the business problems they are trying to solve and help develop and prioritize the best-suited analytics solutions.
  • Collaborate in cross-functional teams and share ideas to solve complex business problems.
  • Build strong partnerships with peers across the organization to support project goals and boarder team needs.
  • Oversee the build of predictive models using advanced analytics techniques including GLMs, natural language processing, and machine learning.
  • Develop powerful insights using a variety of analytical tools, techniques, and technologies, and deliver results into the business which drive business decisions.
  • Discover, explore and analyse internal and external datasets for the purpose of developing advanced analytics models.
  • Help establish best practices and repeatable processes for the Strategic Analytics team.
  • Provide thought leadership on new, innovative techniques, approaches and software.
  • Guide, support, mentor and develop the growing team of predictive modelers and data scientists.

Role Requirements & Skills,  Skills / Competencies

  • Ability to design, build and implement statistical models, with an understanding of a range of analytical techniques such as predictive modelling, NLP and data mining.
  • Data manipulation and analytical skills in languages such as Python, R and / or SQL.
  • Knowledge of modern visualization tools such as PowerBI is a plus.
  • Familiarity with cloud-based platforms such as Databricks, Snowflake and Azure is an advantage, but not essential.
  • Effective task / project management and general organization skills.
  • Excellent verbal and written communications skills; ability to convey complex concepts to technical and non-technical people across the organization.
  • Exceptional teamwork skills required to play a key role in cross-functional teams. Ability to collaborate and build trusting relationships with business partners.
  • Natural curiosity to understand the world around you and question as needed.
  • Comfortable handling ambiguous concepts and breaking down complex problems into manageable pieces.
  • Ability to apply critical thinking and creative problem-solving skills.

Qualifications

  • Degree in statistics, mathematics, engineering or similar quantitative ?elds; or signi?cant experience in advanced data analytics

Essential Experience

  • Experience in advanced analytics roles, a significant portion of which should be in the insurance industry.
  • Experience working in an analytical role within an insurance claims environment is an advantage.
  • Hands-on experience developing and deploying real-time predictive models.
  • Experience delivering business value from small or non-standard data sets.

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