Location - London or Milton Keynes (minimum of two days a week in the office. You can do more than two days if preferable)
Reporting to - Interim Data and Technology Team Lead
Band - 3.2
Salary - £57,000 to £62,000 (depending on location and proven ability)
Working hours - Full time (9 day fortnight)
Contract type/duration - Permanent
Closing date - 19th January 2025
Overview
We're looking for a highly motivated and collaborative data scientist that wants to use their skills to help increase resilience to climate change. You'll be working as part of a cross-functional and cross-organisational team of innovators, researchers, and network operators to develop market-ready digital technologies to make the UK's infrastructure system resilient against climate change and extreme weather.
Purpose of the role
We're looking for an individual with deep technical knowledge to lead the development of our Python modelling codebase. The codebase includes support for: Bayesian risk modelling of assets against climate hazards and their mitigations; network modelling of the cascading risk of asset failures across infrastructure systems; economic modelling of the economic, social, and environmental costs of failure and mitigation; decision intelligence to optimise network mitigation and investment strategies; and network resilience analytics. These services will be deployed to interface with a distributed technology stack (digital twin) developed collaboratively with our partners.
What You'll Be Doing
1. Leading development and design of our Python modelling codebase
2. Interpreting user and product requirements, ensuring best practices across the team
3. Building quick prototypes, developed into production-ready deployments through iteration
4. Planning development into sprint cycles, managing dependencies and proactively addressing risks
5. Working collaboratively in cross-functional teams following agile principles
6. Mentoring junior colleagues as the programme evolves
7. Contributing to team discussions and fostering a culture of knowledge sharing
8. Continuously learning and upskilling to meet programme requirements
9. Communicating progress and outcomes through various formats
10. Upholding CPC's values, ensuring an ethos of equity, inclusivity, and diversity
11. Committing to equal opportunities and ethical practices in all work aspects
Requirements
Essential
1. Qualifications in a scientific, mathematical, or engineering subject or equivalent experience
2. Significant work experience applying data science to real-world projects
3. Day-to-day working knowledge of Python and data science libraries
4. Understanding of core concepts in probability and statistics
5. Experience of quickly learning new methods
6. Experience with agile software development
7. Experience turning research ideas into production code
8. Clear communication to both technical and non-technical stakeholders
9. Pragmatic and outcomes-focused, with problem-solving aptitude
10. Enjoy forming relationships and inspiring teams around a common purpose
Desirable
1. Masters or PhD in a numerate or scientific discipline
2. Knowledge of network science and geospatial methods
3. Knowledge of Monte Carlo methods and Bayesian networks
4. Knowledge of optimisation and decision support methods
5. Knowledge of economic modelling and cost-benefit analysis
6. Awareness of climate resilience and adaptation
Benefits
1. 9 day fortnight for everyone
2. 23.5 holiday entitlement with pro-rata calculations for part-time employees
3. Competitive pension with up to 10% company contribution
4. Two paid days of volunteering leave per year
5. Employee Assistance Programme (EAP) providing 24/7 support
6. Cycle to Work Scheme
7. Cash Health Plan for essential healthcare expenses
8. Payroll Giving scheme for charitable contributions
9. Discounts from a variety of retailers
10. Mortgage Advice benefit
Employment here is based solely upon individual merit and qualifications directly related to professional competence. We strictly prohibit unlawful discrimination or harassment on the basis of any protected characteristic. #J-18808-Ljbffr