Data Scientist

TEC Partners; Lincoln; On-site; GBP 45,000 - 70,000; Full time

Job summary

A leading tech firm in England seeks a Data Scientist to establish a quantitative foundation for a trust and validation framework in autonomous systems. The role involves designing statistical methodologies, developing metrics for evaluating system performance, and optimizing algorithms for large-scale deployments. Ideal candidates will hold an advanced degree in a related field and possess strong statistical expertise and programming skills.

Qualifications

• Strong foundation in statistical methods, experimental design, and measurement frameworks.
• Experience applying quantitative approaches to complex system evaluation.
• Skilled in Python, statistical tools, and data analysis libraries.

Responsibilities

• Design statistical frameworks to validate autonomous system performance.
• Develop mathematical models to quantify trust, reliability, and performance.
• Collaborate with verification and simulation teams to define evaluation standards.

Skills

Statistical methods

Data visualization

Python

Education

Advanced degree in statistics, data science, applied mathematics

Tools

Statistical tools

Data analysis libraries

Job description

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We're looking for a Data Scientist to help establish the quantitative foundation of a cutting-edge trust and validation framework for autonomous systems. In this role, you'll design rigorous statistical methodologies to evaluate system performance, develop confidence and reliability metrics, and support high-scale deployment with robust measurement systems. Your work will be critical in validating performance in high-stakes domains and enabling data-driven decisions as the platform scales from early users to millions of interactions per month.

Responsibilities

Design statistical frameworks to validate autonomous system performance with academic rigor

Develop mathematical models to quantify trust, reliability, and performance in complex domains

Build autoscaling algorithms for compute resource optimization at scale

Create projection models for quota growth and capacity planning across multi-region deployments

Establish methodologies to measure system composition, including dynamic and contextual behavior

Design systems for context traceability and statistical validation of reasoning pathways

Develop confidence calculation methods across simulation runs and deployment conditions

Create judge coverage frameworks for comprehensive performance evaluation

Define metrics tied to interpretability, safety, and business outcomes

Design attribution systems that identify key components contributing to system performance

Model capability expansion to measure growth while maintaining reliability

Collaborate with verification and simulation teams to define evaluation standards

Contribute to academic publications and technical content showcasing scientific rigor

Work with engineering teams to implement statistical measurement systems in production

Qualifications

Advanced degree in statistics, data science, applied mathematics, or related field

Strong foundation in statistical methods, experimental design, and measurement frameworks

Experience applying quantitative approaches to complex system evaluation

Background in building performance metrics for AI or software systems

Proficient in confidence intervals, variance analysis, and statistical validation

Experience designing experiments to quantify behavior across variable conditions

Skilled in Python, statistical tools, and data analysis libraries

Ability to connect metrics to business impact and technical performance

Experience with data visualization for communicating complex concepts

Academic or industry publication experience is a plus

Passion for scientific rigor and trustworthy evaluation in AI systems