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About the Role

Drive and implement data science tools and methods to harness data for customer solutions. Act as a subject matter expert, articulating advanced data and analytics opportunities through data visualization. Identify opportunities to support external customers using data science expertise.

Responsibilities

Understand business stakeholder requirements and needs.
Develop relationships with business stakeholders.
Form hypotheses and identify suitable data and analytics solutions.
Maintain and develop external curiosity around new and emerging trends in data science.
Keep up-to-date with emerging trends and tooling and share updates.
Proactively bring together statistical, mathematical, machine-learning, and software engineering skills.
Implement ethically sound models end-to-end.
Apply software engineering and a product development lens to complex business problems.
Work with and lead direct reports and wider teams in an Agile way.
Use data translation skills to define business questions, problems, or opportunities.
Select, build, train, and test complex machine models.
Consider model valuation, model risk, governance, and ethics.
Scale models.
Deliver complex technical solutions aligned with business objectives.
Communicate methodologies and outcomes to non-technical stakeholders.
Manage ML, AI models in production.
Manage risk and governance.

Requirements

Evidence of project implementation and work experience in a data-analysis-related field within a multi-disciplinary team.
Experience with statistical software, database languages, big data technologies, cloud environments, and machine learning on large data sets.
Experience developing and managing the full model development life cycle of machine learning and AI products from concept to production.
Ability to demonstrate leadership, self-direction, and a willingness to teach and learn.
Demonstrable capability to deliver complex technical solutions aligned with business objectives.
Effective communication of methodologies and outcomes to non-technical stakeholders.
Strong understanding of statistical models including LASSO, Ridge, and Elastic Net.
Understanding of how statistical models can drive pricing strategies of financial products.
Understanding of simulation techniques and core concepts of deep learning and Bayesian statistics.
Expertise in developing Gen AI and Agentic AI tools for chatbots.
Understanding of workflows and evaluation methods to measure and monitor performance at scale.
Experience with CI/CD, DevOps, and model monitoring.
Strong risk management and governance awareness.
Experience with cloud technology such as AWS.
Fluency with Python and SQL.
Ability to self-manage, take initiative, and demonstrate a proactive approach to work.
Effective verbal and written communication skills.
Ability to adapt communication style to a specific audience.

Skills

Data Science
Data Visualization
Statistical Modeling
Machine Learning
Software Engineering
Product Development
Agile Methodologies
Data Translation
Model Development Life Cycle
Gen AI
Agentic AI
CI/CD
DevOps
Model Monitoring
Risk Management
Governance
AWS
Python
SQL
LASSO
Ridge
Elastic Net
Deep Learning
Bayesian Statistics

Location

Edinburgh
London

Work Type

Hybrid
Work from home
Full-time

Experience Level

Subject Matter Expert
Leadership

Education Level

Undergraduate degree in a quantitative discipline
Master's degree in a quantitative discipline
Equivalent practical experience