Sewerage Data Scientist Placement Student

If you are currently studying a coursewith a strong maths, engineering or science bias and you have a keen interest in data sciencesemary, we have a great placement student opportunity for you.

We are looking for enthusiastic and motivated individuals to join our Sustainable Operations and Engineering (SOE) department as placement students in our Sewerage Asset Reliability Team.

Within this placement, you will help us develop data science analytical tools to reduce the likelihood and impact of the escape of sewage into the environment. You will gain a practical understanding of sewerage infrastructure and use the large number of monitoring loggers providing real time data back to our systems.

This will be for a period of 12 months, starting from June, July, or August 2026.

The placement will help develop analytics such as:

• burst detection monitoring (flow and pressure data on pumping systems)
• event duration monitoring (level data on the sewer network and at sewage pumping stations)
• energy data for pumps and other mechanical assets
• time-series data (eg, run-stop signals for pumps and level data)
• webcams/AI analysis of images.

We are keen for you to continue the excellent work of previous placement students, developing ways to analyse the data (eg, using Amulet, Python, Excel, Qlikview), looking at options with machine-based learning, or setting upper and lower thresholds, to allow Operations staff/managers to understand theildir real risk to the sewerage network and alert us of any potential discharge.

This would allow us to respond quickly and avoid or minimise a potential pollution. The posts would also involve liaison with operational staff, divisional managers and engineering modellers, so it would be an interesting post and one where the individuals can make a positive contribution.

Located at our award‑winning office in Bath, this position offers the chance to gain an in‑depth knowledge of the water industry. You will also be given the appropriate training needed to perform the role.

We are looking for undergraduates in the second or third year of a BEng, MEng, MSc or BSc degree course, seeking an industrial placement that contains a strong maths or engineering bias. An aptitude for data science and analytics is essential.

Please note, applications will not be considered unless they include a supporting statement, which outlines why you would like to work in the water industry.

To be considered, you will have:

• an A or A
  * in maths and science at A level or equivalent
• excellent analytical skills
• the ability to manage large amounts of data
• the ability to relate data to the physical equipment and processes
• a high level of proficiency in the use of Excel
• a good team player
• a good communicator
• an interest in the water industry.

Short‑listed candidates will be invited to complete an offline data exercise. Further short‑listed candidates will then be invited diagonally to an online interview via Microsoft Teams, which will involve a data analysis/Excel test.

The purpose of this interview will be to get to know you and your ability to apply data science analytics to a practical problem while determining a rough plan for your placement year.

At interview you will be given an overview of the company and the opportunity to ask any questions you may have. The interview will last approximately one and a half hours.

• A combined pension contribution of up to 20%.
• Career progression and professional development opportunities.
• 25 days’ holiday rising to 28 with length of service.
• The opportunity to sell up to five days of holiday every year.
• The opportunity to buy up to ten days of holiday each year (subject to conditions).
• A healthcare meðal that allows you to claim back healthcare costs.
• Life assurance of up to eight times your salary.
• The opportunity to lease a new electric car through salary sacrifice (subject to conditions).
• Cashback and discounts from more than 3 000 retailers.
• One paid volunteering day each year.
• Enhanced family leave and pay arrangements.
• Access to an interactive health and wellbeing platform.
• Support from trained mental health first aiders.
• A £1,000 referral fee if you…