Data Solution Analyst

Willis Towers Watson; City Of London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading risk management firm in London is seeking a Data Analyst / Solution Architect to drive solutions around Corporate Risk and Broking data challenges. Key responsibilities include developing predictive models, managing stakeholder relationships, and integrating AI-driven client applications. The ideal candidate holds a relevant degree and possesses strong skills in data analytics, Python, and machine learning. This role offers a comprehensive benefits package and hybrid working options.

Benefits

25 days of annual leave

Private healthcare

Defined contribution pension scheme

Hybrid working options

Volunteering day

Qualifications

• Experience developing AI-driven applications or models.
• Ability to communicate insights and technical concepts to non-technical stakeholders.
• Experience working in agile environments with cross-functional teams.

Responsibilities

• Develop predictive models for broking and revenue forecasting.
• Analyze corporate risk and broking (CRB) data for insights.
• Integrate AI-driven solutions into client applications.

Skills

Data analytics experience

Machine learning skills

Proficiency in Python

Proficiency in SQL

Data visualization skills

Strong communication skills

Analytical problem-solving

Education

Bachelor's or master's degree in data science, Statistics, Computer Science, or related field

Tools

Microsoft Azure/Fabric

scikit-learn

TensorFlow

Tableau

Power BI

Job description

Reporting into Tech Data Leadership this role is pivotal in driving solutioning around Corporate Risk and Broking (CRB) data challenges and developing insights through advanced analytics and AI, developing predictive models and client applications to support risk and broking. The Data Analyst / Solution Architect actively manages stakeholder relationships, ensuring that business needs are translated into actionable data solutions. A key focus is on tracing and documenting data lineage across systems, guaranteeing transparency, compliance, and trust in all data-driven initiatives. The role balances analytics and model development with client application integration operating as a bridge between technical teams and business stakeholders to deliver impactful, high-quality solutions.

Qualifications

The Requirements:

• Bachelor's or master's degree in data science, Statistics, Computer Science, or related field
• Experience in data analytics, machine learning, or predictive modeling
• Proficiency in Python, R, SQL, and ML frameworks (e.g., scikit-learn, TensorFlow)
• Familiarity with Microsoft Azure/Fabric for data processing
• Knowledge of corporate risk and broking (R&B) industry
• Experience developing AI-driven applications or models
• Skills in data visualization (e.g., Tableau, Power BI)
• Ability to work in agile environments with cross-functional teams
• Strong analytical and problem-solving skills for complex datasets
• Proven delivery on analytics or AI projects
• Ability to communicate insights and technical concepts to non-technical stakeholders
• Strong communication and stakeholder management skills

Enjoy a benefits package designed to help you thrive, both professionally and personally. You'll receive 25 days of annual leave plus an extra WTW day to relax and recharge. Our comprehensive health and wellbeing offering includes private healthcare, life insurance, group income protection, and regular health assessments, all giving you peace of mind. Secure your future with our defined contribution pension scheme, featuring matched contributions up to 10% from the company.

We support your growth and balance with hybrid working options, access to an employee assistance programme, and a fully paid volunteer day to make a difference in your community. On top of these, you can opt into a variety of additional perks including an electric vehicle car scheme, share scheme, cycle-to-work programme, dental and optical cover, critical illness protection, and much more. Start making the most of your career and wellbeing with a range of benefits tailored for you.

At WTW, we believe difference makes us stronger. We want our workforce to reflect the different and varied markets we operate in and to build a culture of inclusivity that makes colleagues feel welcome, valued and empowered to bring their whole selves to work every day. We are an equal opportunity employer committed to fostering an inclusive work environment throughout our organisation. We embrace all types of diversity.

We’re committed to equal employment opportunity and provide application, interview and workplace adjustments and accommodations to all applicants. If you foresee any barriers, from the application process through to joining WTW, please email [e-mail].

Responsibilities

The Role:

Analytics & Model Development (≈ 70%) – Creating Insights, Ensuring Data Lineage:

• Collaborate closely with product owners, engineers, and business stakeholders to develop solutions to data related challenges and ensure solutions align with business needs and priorities.
• Develop predictive models for broking and revenue forecasting using corporate platforms (e.g., Python, scikit learn, TensorFlow).
• Analyze CRB data (e.g., client portfolios, market feeds) to generate actionable insights for business stakeholders.
• Build revenue models to optimize R&B financial outcomes.
• Trace and document data lineage across all relevant systems, ensuring data sources, transformations, and usage are transparent and auditable.
• Ensure model accuracy, robustness, and compliance through rigorous testing and validation.

Client Application Integration (≈ 30%) – Enabling AI-Driven Solutions:

• Develop AI-integrated client applications (e.g., automated broking tools) for R&B workflows
• Work with engineers to integrate models into data products and dashboards
• Support data presentation efforts, ensuring insights are actionable for brokers/advisors
• Monitor application performance, incorporating feedback for improvements
• Foster strong stakeholder relationships by gathering feedback, incorporating user needs, and driving continuous improvement.
• Monitor application performance and data flows, proactively addressing issues related to data quality, lineage, and user experience