Data Scientist - New

London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist – London - Hybrid

Job description
BDO Regulatory Solutions are currently recruiting for a Data Scientist to join our client, a Regulated firm, based in London.
We are offering an initial 3 month contract starting ASAP with an excellent day rate, employed via an Umbrella company.

About the role:
We are looking for talented and experienced data scientists with experience to join our programme. To work with the existing delivery team to deliver models, documentation and associated productionised services. Solid knowledge and experience of AI and ML is essential

Key responsibilities include;
Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering
SQL: For querying structured data sources
Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models
Machine Learning Deployment: Familiarity with containerised deployment (e.g. Podman, SageMaker, DSW pipelines)
Version Control (Git): To maintain reproducible and collaborative workflows
Time-Series Analysis: To assess risk trends over financial years
Exploratory Data Analysis (EDA): To spot early signals or risk clustersDesirable Experience:
Rank Aggregation/Ensemble Techniques: Understanding methods like Robust Rank Fusion (RRF)
Model Explainability Tools: e.g. SHAP, LIME to support interpretability
Experience with Model Monitoring & Drift Detection
Experience in RegTech / FinCrime / Data-led Supervision Projects is a plus
Experience developing solutions for record linkage and/or network analytics tasks
Experience with graph query languages (e.g., Gremlin, Cypher), graph database platforms (e.g., Neptune, Neo4j), and/or graph visualisation platformsAdditional Information:
Location: London - Hybrid
Duration: Initial 3 months
Day Rate: Competitive, employed via an Umbrella company.

Are you ready to join the team? Click on the link to apply

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.