Quantitative Insights Architect

Lead Forensics; Portsmouth; Hybrid; GBP 42,000 - 62,000; Full time

Benefits offered by this job

Hybrid work in Cosham office

Competitive salary and benefits

Volunteer days and charity events

Job summary

Lead Forensics is seeking a Quantitative Research Analyst in Portsmouth, blending hands‑on modelling with data analysis to shape a new analytical capability. The role involves designing structured models, turning complex inputs into clear outputs, and collaborating with Product, Engineering and leadership teams.

The ideal candidate has a strong quantitative background, advanced Excel skills and experience with Python/SQL/R for analysis.

Qualifications

• Strong quantitative background in maths, finance, economics or engineering.
• Advanced Excel modelling skills.
• Experience building analytical models or structured frameworks.
• Experience using Python, SQL or R for analysis is beneficial.
• Ability to work with complex or ambiguous data and draw clear conclusions.
• Comfortable combining analysis with interpretation and judgement.
• Confident presenting findings and explaining your thinking.
• Curious, detail‑oriented and persistent.

Responsibilities

• Building and refining analytical models and decision‑support frameworks.
• Working with multiple datasets and shaping them into structured outputs.
• Developing logical approaches to ranking, weighting and interpretation.
• Analyzing outputs to identify patterns, anomalies and areas for improvement.
• Applying judgement to interpret findings and assess what is meaningful.
• Preparing clear analysis and sharing insights with internal stakeholders.
• Becoming the internal point of reference for this area over time.

Skills

Strong quantitative background

Advanced Excel modelling

Data analysis

Tools

Excel

Python

SQL

R

Job description

Lead Forensics is seeking a Quantitative Research Analyst in Portsmouth, blending hands‑on modelling with data analysis to shape a new analytical capability. The role involves designing structured models, turning complex inputs into clear outputs, and collaborating with Product, Engineering and leadership teams.

The ideal candidate has a strong quantitative background, advanced Excel skills and experience with Python/SQL/R for analysis.