Senior Data Analyst

Company Description

Verisk Underwriting is a division of Verisk Analytics. We are a leading data and analytics supplier to the insurance industry as well as many others such as emergency services, government, utilities, telecom network operators, finance and real estate.   

A key part of our business is harnessing geospatial data analytics to provide land and property insights. Reliable insight on property and land use can improve decision making and speed up processes. For example, having knowledge of properties with basements can identify those at risk of greater damage when flooding occurs. Knowledge of the size and age of a property as well as the number of rooms can help with the valuation of the property and estimating the likely number of occupants.  

 Another key area is the creation of sophisticated risk models to assist insurers with risk selection and accurate pricing. Our range of models is broad spanning residential and commercial property perils, motor insurance, travel, pet and health insurance.  

To feed our property insights and risk models we source many diverse datasets covering high resolution weather data, property attributes, business activities and financial data, insurance claims and policies, medical information, aerial imagery and geodemographic data.  

Job Description

Data is key to our business. We are looking for a motivated, independent and well organised individual who enjoys working with data but is equally interested in building a strong understanding of how the data is used by both internal and external stakeholders.  

This role will have primary responsibility for analysing and assessing the quality of property data sources in the UK. The quality assessment will be based on the accuracy, completeness and consistency of the data as well as the degree to which it meets the needs of its’ users.  

The DA will be responsible for the evaluation, processing and reconciliation of different property datasets and producing a consolidated high-quality dataset. Validation of our data is critical and the postholder will be responsible for regular data quality reporting and maintenance and continually seeking ways to improve data quality. 

The DA will work with the product, sales, and analytics teams in responding to queries on data issues, preparing data products POCs for external clients, and prioritising which areas need improvement and attention. They will also be responsible for reviewing and recommending improvements to the design of our other property products which leverage this data. 

The role will make use of large datasets with tens of millions of records and so the postholder will need to have excellent technical skills and the ability to code in both Python and Sql. It will require a strong attention to detail to ensure the effective management of our large and complex datasets.  

 Role Responsibilities  

• Assess the quality of various property datasets including by evaluating the consistency with other sources and external high-level statistics as well as the self-consistency of the dataset.  

• Review and develop the logic to combine various datasets to maximise the coverage and credibility of the final combined dataset 

• Assist other members of the team in understanding the strengths and weaknesses of the property data and answering specific queries about the data. 

• Identify how data errors should be corrected and design sophisticated validation checks. 

• Keep records of issues and feedback to technology and product teams on processing improvements in automated pipelines. 

• Feedback to data scientists where analytics modelling could potentially enhance property datasets. 

• Extract data for prospective customers to test property products. 

• Ad hoc data processing projects. 

• Assist with research, identification and sourcing of new datasets. 

• Develop an understanding of how the data is used by internal and external clients to ensure that it is fit for purpose 

• Aid in the prioritisation of improvements to the data by balancing out client need versus feasibility and effort required 

Qualifications

• Knowledge of SQL or other data querying languages  

• Knowledge of Python programming and visualisation 

• Experience working with data, including processes for data validation and quality control  

• An understanding of data management fundamentals, including concepts such as data dictionaries, data models, validation, and reporting.  

• Experience in troubleshooting data quality issues   

Additional Information

In 2022, Verisk received Great Place to Work® Certification for our outstanding workplace culture