Data Scientist

Vallum Associates
London, United Kingdom
12 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Faculty AI London, United Kingdom
Hybrid

Data Scientist, Integrity Measurement

OpenAI London, United Kingdom
Hybrid

Data Scientist – Cross Indication (12-month

Relation Therapeutics London, United Kingdom
£40,000 – £60,000 pa On-site

Data Scientist / Algorithm Engineer

PhysicsX United Kingdom

Commercial Data Scientist

Synthesia London, United Kingdom
Remote

Senior Data Scientist

Faculty AI London, United Kingdom
£40,000 – £70,000 pa Remote Clearance Required
Posted
13 May 2025 (12 months ago)

Role- Data Scientist

Location: London, UK

Type of job : Contract

Work mode : Hybrid- 2 days onsite in a week

Responsibilities:

* Explore, clean, and analyse large, complex datasets to uncover patterns, trends, and opportunities that drive actionable insights.

* Develop, train, and validate machine learning, statistical, and predictive models that solve real business problems and deliver measurable impact.

* Design and run experiments (A/B tests, hypothesis tests, simulations) to evaluate ideas, quantify outcomes, and guide decision‑making.

* Collaborate with data engineers, analysts, product managers, and domain experts to translate business requirements into well‑defined modelling tasks.

* Build end‑to‑end ML pipelines—from feature engineering and preprocessing to deployment‑ready model outputs.

* Apply advanced techniques such as NLP, time‑series forecasting, anomaly detection, optimisation, or LLM/GenAI methods where relevant.

* Implement model evaluation frameworks using offline metrics, cross‑validation, online experiments, and human‑in‑the‑loop feedback loops.

* Communicate insights clearly through dashboards, visualisations, written summaries, and presentations tailored to technical and non‑technical stakeholders.

* Ensure models are interpretable and explainable where required, providing transparency into key drivers and assumptions.

* Work with engineering teams to deploy models into production, monitor performance, and retrain or recalibrate as data and conditions change.

Essential skills:

Hands-on experience with GenAI, Gemini or Open source LLMs and develop GenAI applications for Code Translation, Text Extraction, Summarisation and SDLC Optimization etc.

* Hands-on Experience with AI Agents, Chat bots, RAG (Retrieval-Augmented Generation), and vector databases. ( PG vector / croma DB )

* Hands-on Experience with GenAI Performance Evaluation tools like Pegasus, Ragas, DeepEval

* Create Conversational Interface with React JS or other Frontend components, Develop and deploy AI agents using LangGraph and ADK, A2A, MCP

* Strong programming skills in Python (experience with LangChain/LangGraph / LangSmith frameworks) and TypeScript ( preferable )

* Solid understanding of LLMs, prompt engineering, and graph-based workflows.

* Knowledge and implementation of Input and Output guardrails in addressing Hallucination, PII filtering, HAP and Bias etc.

* Implemented security best practices, Experience to address spikes and Denial of wallet attacks, DDoS attack and other Spike arrest strategies

* Knowledge of API Gateways and ISTIO , ability to Diagnose and intercept failures in End to End communication

* Hands-on Experience with API Development and Microservices architecture

Desirable experience:

* Strong experience applying machine learning, statistical modelling, and predictive analytics to real‑world business problems.

* Collaborate with cross-functional teams to ability to resolve end to end connectivity and Data Integrations

* Experience working with large, complex datasets, including data cleaning, feature engineering, and exploratory data analysis.

* Familiarity with LLMs, NLP techniques, and GenAI frameworks, including embeddings, prompt engineering, or fine‑tuning.

* Experience building end‑to‑end ML pipelines, including model validation, optimisation, deployment, and monitoring.

* Understanding of MLOps practices, including model versioning, model registries, CI/CD for ML, and automated training/inference workflows.

* Ability to translate business problems into analytical tasks and communicate insights in a clear, concise manner to technical and non‑technical audiences.

* Knowledge of data governance, including data quality, lineage, ethics, privacy considerations, and responsible AI principles.

* Comfort working with cloud platforms (GCP preferred) for model training, deployment, and scalable compute.

* A growth‑oriented mindset with enthusiasm for exploring new algorithms, tools, and emerging AI/ML techniques

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.

Where to Advertise AI Jobs in the UK (2026 Guide)

Advertising AI jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

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.