Lithe Consulting Ltd
Senior Data Scientist

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Senior Data Engineer / Data Analyst
Location: hybrid 3 days per week onsite in either London or Sheffield (can be negotiated to 2 days per week for exceptional candidates in exceptional circumstances)
Remuneration: either £450/day INSIDE IR35, or £90-£100k permanent employed
Description
Our client is a fast-growing international consultancy specialising in data, AI, and advanced analytics for major financial institutions. With programmes running across the UK and Europe, they are expanding their team to support large-scale data science and modelling initiatives.
This is a Senior Data Scientist/Analyst role within their global banking client’s developer experience team, supporting a new organisation-wide analysis initiative. This role sits at the intersection of data engineering and analytics, and requires strong, critical data processing and presentation skills to translate raw, ambiguous data into insights that directly drive strategic decisions across the organisation.
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.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Essential Requirements
Stakeholder Management & Analysis
- Drive organisation-wide analysis, autonomously conducting gap analyses and translating ambiguous business needs into clear technical roadmaps.
- Manage expectations directly with users and data owners, keeping delivery aligned to business priorities.
Data Engineering
- Architect, build, and scale robust data pipelines using Python and SQL across platforms such as BigQuery and PostgreSQL.
- Work within established team standards for data extraction, complex aggregation, and resilient exception management, contributing to their ongoing improvement.
Statistical Analysis & Quality
- Apply advanced, critical quantitative methods (Pandas, NumPy) to process raw data and derive actionable insights.
- Implement automated frameworks to ensure enterprise-grade data quality and continuous validation.


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Strategic Reporting
- Design high-impact visualisation dashboards using Looker Studio.
- Go beyond basic reporting to translate raw statistical findings into insights that clearly drive strategic business decisions.
Engineering Excellence & Delivery
- Developer Experience & DORA metrics: A working knowledge of DORA metrics (Lead Time to Deploy, Release Frequency) will be nice. Knowledge of Development Practices/Pipeline/Methodologies will be needed.
Nice to Have
- Knowledge of workflow toolkits such as Apache Airflow, Dagster, or similar.
- Active use of modern LLMs (Claude, GitHub Copilot) to accelerate development and pioneer AI-assisted coding practices within the team.
- Version control: Enforce version control best practices (Git/GitHub), lead code reviews, and integrate pipelines into CI/CD workflows.
- Cloud architecture: Prior experience deploying, optimising, working with cloud environments.
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