CEERISK Consulting Ltd
Data Scientist

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Company Description
CEERISK Consulting is a multidisciplinary firm that helps corporations identify engineering risks and develop solutions to control hazards and reduce the impact of costly accidents. The company combines deep knowledge of failure mechanisms across systems and equipment with a strong understanding of evolving global standards. CEERISK focuses on the uncertainties created by complex new technologies and globalization, offering expert risk assessment and management strategies. By integrating an understanding of emerging technologies, failure modes, and local business and cultural environments, CEERISK brings greater certainty to the construction, energy, and engineering sectors.
Role Description
This is a full-time, on-site Data Scientist role based in Kingston Upon Thames. The Data Scientist will collect, clean, and analyze structured and unstructured data to support engineering risk assessments and decision-making.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Responsibilities


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- Building statistical and machine learning models
- Developing predictive analytics
- Translating complex data insights into clear recommendations for consultants and clients
- Creating data visualizations and reports
- Collaborating with multidisciplinary teams on risk studies
- Contributing to the development of tools and methodologies that improve hazard identification and loss prevention
- Helping maintain data quality
- Documenting analytical processes
- Staying current with relevant technologies and standards
Qualifications
- Strong foundation in Data Science and Data Analytics to design, implement, and evaluate data-driven solutions
- Proficiency in Statistics and Data Analysis for building robust models and performing rigorous quantitative assessments
- Experience with Data Visualization to present complex findings clearly to technical and non-technical stakeholders
- Relevant experience with programming languages and tools commonly used in data science (e.g., Python, R, SQL, modern BI tools)
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field
- Ability to work collaboratively in a multidisciplinary environment and communicate technical concepts effectively
- Knowledge of engineering, construction, or energy domains, and familiarity with risk assessment methodologies, is an advantage
- Strong problem-solving skills, attention to detail, and commitment to maintaining high data quality and integrity
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