Quantitative Modeling Intern – Energy Forecasts

Low Carbon Contracts Company; Leeds; On-site; GBP 27,000 - 33,000; Full time

Benefits offered by this job

Annual bonus up to 10%

25 days annual leave

Pension contribution up to 8%

Study support

Volunteer days

Cycle to work

Employee assistance

Job summary

Low Carbon Contracts Company (LCCC) invites applications for a Quantitative Development Intern in Leeds. The role focuses on developing forecasting and analytical models within the Analytics team, contributing to UK Net Zero initiatives.

The internship spans 6-12 months, with a 2 days/week in-office requirement and 37.5 hours per week. Ideal candidates are undergraduate or masters students with strong computing and statistical modelling skills, a 2:1 STEM degree, and hands-on Python/OOP

Qualifications

• An expected 2:1 undergraduate degree in STEM subjects.
• Ability to convey complex technical concepts to non-technical audiences in a meaningful way.
• Experience with Python and Object Oriented Programming.

Responsibilities

• Explore and clean datasets required for modelling purposes.
• Design and build short and long-term energy models used in forecasting, analysis and for generating insights that support various strategic initiatives.
• Testing and deploying updates to the models.
• Producing high quality technical documentation.
• Identifying and streamlining inefficient processes.
• Supporting other teams with modelling, analysis and automation.

Skills

Python

Object Oriented Programming

Forecasting

Data analysis

Education

2:1 STEM degree

Tools

Git

Cloud computing

Job description

Low Carbon Contracts Company (LCCC) invites applications for a Quantitative Development Intern in Leeds. The role focuses on developing forecasting and analytical models within the Analytics team, contributing to UK Net Zero initiatives.

The internship spans 6-12 months, with a 2 days/week in-office requirement and 37.5 hours per week. Ideal candidates are undergraduate or masters students with strong computing and statistical modelling skills, a 2:1 STEM degree, and hands-on Python/OOP