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# Senior Data Scientist

- **Company:** Leidos, Inc.
- **Location:** Bristol, UK (Remote available)
- **Experience:** Expert
- **Salary:** £74,845.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Vision, Big Data, Cloud Computing, Data Cleansing, Apache Hadoop, Python (Programming Language), Machine Learning, NumPy, Power BI, Tensorflow, Azure Machine Learning, Tableau (Software), Feature Engineering, Pytorch, Apache Spark, Deep Learning, Pandas, Scikit Learn, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** August 5, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5829129044

## About the Role

* Experience in data science, machine learning, or applied analytics
 * Strong proficiency in Python and common ML libraries (pandas, NumPy, scikit-learn, TensorFlow, PyTorch)
 * Experience designing, training, and evaluating machine-learning models
 * Solid understanding of statistical methods, predictive modelling, and experimental design
 * Experience working with large or complex datasets, including data cleansing and feature engineering
 * Ability to communicate analytical concepts clearly to non-technical stakeholders
 * Experience working in an agile delivery environment
 * Strong problem-solving skills and attention to detail

Desired Skills:

 * Experience with cloud-based ML services (AWS SageMaker, Azure ML, Databricks)
 * Familiarity with MLOps practices and model lifecycle management
 * Experience with NLP, deep learning, or computer vision
 * Knowledge of data visualisation tools (Power BI, Tableau)
 * Exposure to big-data technologies (Spark, Hadoop)
 * AWS certifications
 * Experience supporting government or highly regulated environments

## Description

* Designing, developing, and validating statistical models and machine-learning solutions
 * Conducting exploratory data analysis and feature engineering to uncover insights and support decision-making
 * Working closely with data engineers to ensure high-quality, scalable data pipelines for modelling
 * Translating analytical findings into clear, actionable recommendations for technical and non-technical audiences
 * Supporting the development of analytical roadmaps, risk identification, and mitigation planning
 * Contributing to the operationalisation and monitoring of models in production environments
 * Evaluating emerging tools, frameworks, and methodologies to enhance analytical capability
 * Providing guidance and informal mentorship to junior data scientists and analysts
 * Ensuring responsible, ethical, and secure use of data and AI


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