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Data Scientist
Ceox —Remote
- Remote
- DevOps
- Master's degree
- SQL
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4h

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Data Scientist

Ceox -
Remote

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Job details

Freelance
4 hours ago

Qualifications

Law
DevOps
Master's degree
SQL
Machine learning
Metadata
Communication skills
Python

Full job description

Data Scientist (Forecasting | LLM Evaluation | Python/SQL)

Contract (OPutsideIR35)| Remote | UK Public Sector Project

Overview

We are seeking a Senior Data Scientist to work within a multi-disciplinary team to develop and deploy modelling and forecasting capability within a large-scale organisational environment. This role involves translating analyst and business requirements into well-defined modelling problems, building and evaluating time series and supervised learning solutions, and assessing the outputs of large language models for accuracy and reliability. The Data Scientist will collaborate closely with technical and non-technical stakeholders, communicating modelling approaches and results clearly at each stage of delivery.

About the Role

An experienced Data Scientist who can confidently translate ambiguous business requirements into rigorous modelling problems, build and evaluate forecasting and machine learning solutions, and assess the outputs of large language models with the same discipline applied to traditional statistical methods.

Key Responsibilities

Translate requirements from analysts and business stakeholders into problems that can be addressed through statistical or machine learning approaches.
Design, build, and validate time series forecasting models using both statistical methods (e.g. ARIMA) and machine learning approaches (e.g. random forest, deep learning).
Apply supervised learning techniques to relevant business problems, with strategies such as active learning used where appropriate to improve model performance.
Carry out feature engineering to support both forecasting and supervised learning models.
Evaluate the outputs of large language models, applying methods such as prompt engineering, retrieval-augmented generation (RAG), and metadata to support knowledge base accuracy.
Communicate modelling approaches and assumptions to stakeholders before development, and present results and their implications iteratively as work progresses.
Develop and maintain Python and SQL code under version control, working to DevOps practices for testing, deployment, and collaboration; document modelling decisions, assumptions, and evaluation criteria to organisational standards.

Mandatory Requirements

Demonstrated experience in time series analysis, including machine learning approaches (feature engineering, deep learning, random forest) and statistical approaches to forecasting (e.g. ARIMA).
Demonstrated experience in supervised learning approaches, with experience of strategies such as active learning considered an advantage.
Proven ability to translate requirements from analysts into a problem that can be solved through modelling, and to communicate modelling approaches and outcomes clearly before, during, and after development.
Experience evaluating the outputs of large language models, including the use of approaches such as prompt engineering and retrieval-augmented generation (RAG), and the use of metadata to support a knowledge base.
Strong working knowledge of Python and SQL.
Essential experience with version control and working within a DevOps approach to development and deployment.
Ability to work with both structured and unstructured data sources to support model development.

Desirable

Strong stakeholder communication, able to explain modelling choices and results to non-technical audiences.
Analytical and solution-focused mindset, comfortable working with ambiguity.
Able to work independently, take ownership and drive progress.
Commitment to clean, well-documented, and reproducible code.
Adaptable, proactive, and comfortable working in dynamic delivery environments.

Soft Skills

Prior experience working within UK Public Sector environments or with Government Digital Standards.
Experience deploying models within a cloud data platform such as Databricks.
Familiarity with MLOps practices for model monitoring, retraining, and lifecycle management.

Contract Details

Contract Type: Freelance / Contract (Outside IR35)

Location: Remote (UK-based candidates only)

Start Date: ASAP

Clearance: Candidates must be eligible for UK BPSS check

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