What Jobs are available for Data Science in Bristol?

• Assist in the collection, cleaning, and preprocessing of large datasets from various sources.
• Perform exploratory data analysis (EDA) to identify patterns, trends, and insights.
• Develop and implement machine learning models for predictive analytics and forecasting.
• Create compelling data visualisations and dashboards to communicate findings to stakeholders.
• Support the development and testing of new analytical tools and methodologies.
• Collaborate with cross-functional teams to understand business needs and translate them into data-driven solutions.
• Document methodologies, processes, and results clearly and concisely.
• Participate in team meetings, contributing ideas and insights.
• Learn and apply new data science techniques and technologies.
• Assist in A/B testing design and analysis.
• Contribute to the ongoing improvement of data quality and governance.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• Strong foundational knowledge of statistical concepts and machine learning algorithms.
• Proficiency in programming languages such as Python or R.
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
• Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Tableau, Power BI).
• Excellent analytical and problem-solving skills.
• Strong written and verbal communication skills, with the ability to explain technical concepts to a non-technical audience.
• Self-motivated, curious, and eager to learn in a remote setting.
• Ability to work independently and manage time effectively.
• Understanding of SQL and database principles is desirable.
• Previous internship or project experience in data analysis is a plus.

• Lead the design, development, and deployment of scalable machine learning models and algorithms.
• Mentor and guide a team of ML engineers, fostering technical excellence and professional growth.
• Architect robust MLOps pipelines for model training, validation, deployment, and monitoring.
• Collaborate closely with data scientists, software engineers, and product managers to define project requirements and deliver high-impact solutions.
• Identify and evaluate new technologies, tools, and methodologies to enhance ML capabilities.
• Ensure the performance, scalability, and reliability of ML systems in production environments.
• Conduct rigorous experimentation, A/B testing, and performance analysis to optimize model effectiveness.
• Contribute to research initiatives and stay at the forefront of ML advancements.
• Communicate technical concepts and project status effectively to both technical and non-technical stakeholders.

• MSc or PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• 5+ years of professional experience in machine learning engineering, with a proven track record of delivering production-ready ML systems.
• Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn, etc.
• Extensive experience with cloud platforms (AWS, Azure, GCP) and MLOps tools (e.g., Docker, Kubernetes, MLflow).
• Demonstrated experience in leading and managing technical teams.
• Deep understanding of various ML techniques, including supervised, unsupervised, and deep learning.
• Excellent problem-solving skills and the ability to tackle complex technical challenges.
• Strong communication and collaboration skills.
• Experience with large-scale data processing frameworks (e.g., Spark) is a plus.

• Design, develop, and implement sophisticated machine learning models for predictive analytics, classification, regression, and other AI tasks.
• Conduct thorough data analysis, cleaning, and feature engineering on diverse datasets.
• Explore and prototype new ML algorithms and techniques relevant to business challenges.
• Evaluate model performance rigorously using appropriate metrics and validation strategies.
• Deploy trained ML models into production environments, working with MLOps teams.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical specifications.
• Stay abreast of the latest research and developments in machine learning and artificial intelligence.
• Communicate complex findings and model insights clearly to both technical and non-technical stakeholders.
• Contribute to the team's knowledge base and mentor junior data scientists.
• Ensure the ethical and responsible use of AI and machine learning technologies.

• PhD or Master's degree in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• Proven experience (5+ years) as a Machine Learning Scientist or in a similar role.
• Expertise in programming languages such as Python and proficiency with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong understanding of various ML algorithms, including supervised, unsupervised, and deep learning techniques.
• Experience with data manipulation and analysis tools (e.g., Pandas, SQL).
• Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation abilities.

Lead Machine Learning Operations Engineer - Remote - £70-£0k + Excellent Benefits

We're seeking a Lead Machine Learning Operations Engineer to spearhead the development and optimisation of our cutting-edge data platform. This is a strategic, hands-on leadership role where you'll guide a growing ML Ops team, architect scalable infrastructure, and ensure seamless deployment and monitoring of machine learning models in production.

What you'll be doing as Lead ML Ops Engineer:

• Leading the design and implementation of robust ML Ops pipelines using Azure, Databricks, and Delta Lake
• Architecting and overseeing API services and caching layers (e.g., Azure Cache for Redis)
• Driving integration with cloud-based data storage solutions such as Snowflake
• Collaborating with data scientists, engineers, and product teams to align ML infrastructure with business goals
• Establishing best practices for model deployment, monitoring, and lifecycle management
• Conducting performance tuning, load testing, and reliability engineering
• Managing CI/CD workflows and infrastructure as code via Azure DevOps and GitHub
• Mentoring junior engineers and fostering a culture of technical excellence and innovation

What we're looking for from the Machine Learning Operations Lead:

• Proven experience in ML Ops leadership, with deep expertise in Azure, Databricks, and cloud-native architectures
• Strong understanding of Postgres, Redis, Snowflake, and Delta Lake Architecture
• Hands-on experience with Docker, container orchestration, and scalable API design
• Excellent communication and stakeholder management skills
• Ability to drive strategic initiatives and influence technical direction
• Bonus: experience with Azure Functions, Azure Containers, or Application Insights

Benefits for the Machine Learning Operations Engineer:

• 25 days holiday (rising with service) + bank holidays
• Annual discretionary bonus
• Enhanced pension scheme
• Flexible working and flexi-time options
• Healthcare cash plan
• Electric vehicle salary sacrifice scheme
• Discounts scheme
• Wellbeing app
• Enhanced maternity and paternity leave
• Life assurance (4x salary)
• Cycle to Work scheme
• Employee referral scheme

If you are interested in this position please click 'apply'.

Hunter Selection Limited is a recruitment consultancy with offices UK wide, specialising in permanent & contract roles within Engineering & Manufacturing, IT & Digital, Science & Technology and Service & Sales sectors.

Please note as we receive a high level of applications we can only respond to applicants whose skills & qualifications are suitable for this position. No terminology in this advert is intended to discriminate against any of the protected characteristics that fall under the Equality Act 2010.

For the purposes of the Conduct Regulations 2003, when advertising permanent vacancies we are acting as an Employment Agency, and when advertising temporary/contract vacancies we are acting as an Employment Business.

Machine Learning Operations Engineer - Remote - £50-£0k + excellent benefits

We're looking for a skilled Machine Learning Operations Engineer to join a newly established team working on an exciting data platform project. This is a hands-on role where you'll help build and maintain the infrastructure that supports machine learning models in a live environment.

What you'll be doing as the Machine Learning Operations Engineer:

• Developing and maintaining API services using Azure and Databricks
• Managing caching layers with Azure Cache (Redis)
• Using Delta Live Tables for data processing and analytics
• Integrating with cloud-based data storage solutions like Snowflake
• Collaborating with cross-functional teams in an agile environment
• Supporting analytics, model deployment, and data-driven decision tools
• Conducting performance, load, and end-to-end testing
• Writing pipeline code and managing deployments via Azure DevOps (GitHub)

What we're looking for from the Machine Learning Operations Engineer:

• Solid experience in ML Ops, particularly with Azure and Databricks
• Familiarity with Postgres, Redis, and Snowflake
• Understanding of Delta Lake Architecture, Docker, and container services
• Experience building and orchestrating APIs
• Strong problem-solving and communication skills
• Bonus: exposure to Azure Functions, Containers, or Insights

Benefits for the Machine Learning Operations Engineer:

• 25 days holiday (rising with service), plus bank holidays
• Annual discretionary bonus
• Enhanced Pension scheme
• Flexible working and flexi-time options
• Healthcare cash plan
• Electric vehicle salary sacrifice scheme
• Discounts scheme
• Wellbeing app
• Enhanced mat and pat leave
• Life assurance (4x salary)
• Discounts on insurance
• Cycle to Work scheme
• Employee referral scheme

If you are interested in this position please click 'apply'.

Hunter Selection Limited is a recruitment consultancy with offices UK wide, specialising in permanent & contract roles within Engineering & Manufacturing, IT & Digital, Science & Technology and Service & Sales sectors.

Please note as we receive a high level of applications we can only respond to applicants whose skills & qualifications are suitable for this position. No terminology in this advert is intended to discriminate against any of the protected characteristics that fall under the Equality Act 2010.

For the purposes of the Conduct Regulations 2003, when advertising permanent vacancies we are acting as an Employment Agency, and when advertising temporary/contract vacancies we are acting as an Employment Business.

• Conduct advanced research in machine learning and artificial intelligence.
• Develop, implement, and evaluate novel ML algorithms and models.
• Design and execute experiments to test hypotheses and validate research findings.
• Collaborate with cross-functional teams to integrate ML solutions into products and services.
• Analyze large datasets to extract insights and inform model development.
• Stay abreast of the latest research and advancements in AI/ML.
• Contribute to research publications and presentations.
• Develop prototypes and proof-of-concepts for new AI technologies.
• Mentor junior researchers and engineers.
• Ensure ethical considerations and responsible AI practices are integrated into research.

• PhD or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
• Proven research experience in Machine Learning (publications in top-tier conferences/journals are a strong plus).
• Proficiency in programming languages such as Python.
• Hands-on experience with ML frameworks like TensorFlow, PyTorch, or similar.
• Strong understanding of statistical modeling, data analysis, and algorithm design.
• Experience with deep learning techniques and architectures.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration abilities.
• Ability to work independently and as part of a research team.

• Design, develop, and implement machine learning models and algorithms to solve complex business problems.
• Clean, preprocess, and analyze large, complex datasets from various sources.
• Perform exploratory data analysis to identify patterns, trends, and opportunities.
• Develop and deploy predictive models for forecasting, classification, clustering, and other ML tasks.
• Evaluate and refine model performance, ensuring accuracy, scalability, and efficiency.
• Collaborate with engineering teams to integrate ML models into production systems.
• Communicate findings, insights, and recommendations effectively to both technical and non-technical stakeholders.
• Stay current with the latest advancements in machine learning, artificial intelligence, and data science.
• Mentor junior data scientists and contribute to the team's technical growth.
• Contribute to the development of data infrastructure and best practices.

• Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 5 years of experience as a Data Scientist with a strong focus on machine learning.
• Proficiency in programming languages such as Python or R, and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of statistical modeling, data mining, and machine learning techniques.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Experience with cloud platforms (AWS, Azure, GCP) for ML deployment is desirable.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex technical concepts to diverse audiences.
• Ability to work effectively in a hybrid team environment, balancing independent research with collaborative problem-solving.
• Proven ability to deliver data-driven solutions from conception to deployment.

• Conduct state-of-the-art research in machine learning, deep learning, and related AI fields.
• Develop, implement, and evaluate novel algorithms and models for various AI applications.
• Design and execute experiments to test hypotheses and validate research findings.
• Analyze large datasets to extract insights and inform model development.
• Collaborate with product teams to translate research breakthroughs into practical, deployable AI solutions.
• Stay abreast of the latest advancements in AI and machine learning through literature review and conference participation.
• Publish research findings in top-tier academic conferences and journals.
• Develop and maintain high-quality, well-documented code for research prototypes.
• Mentor junior researchers and contribute to the team's technical growth.
• Contribute to the intellectual property portfolio through patents and internal innovations.
• Work with engineers to integrate research models into production systems.
• Present research findings to both technical and non-technical audiences.
• Identify new research opportunities and propose innovative projects.
• Ensure ethical considerations are integrated into AI development practices.
• Contribute to the vibrant research community within the organization and beyond.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Proven track record of significant contributions to the field of AI/ML, demonstrated through publications, patents, or successful project implementations.
• Expertise in at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong programming skills in Python and experience with relevant libraries.
• Deep understanding of various machine learning algorithms, statistical modeling, and data analysis techniques.
• Experience with large-scale data processing and distributed computing environments.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration abilities, with the capacity to work effectively in a hybrid team environment.
• Ability to work independently on research problems and drive projects forward.
• Experience in (mention a specific relevant area, e.g., NLP, Computer Vision, Reinforcement Learning) is a significant advantage.

• Write clean, efficient, and well-documented code (primarily Python) for ML projects.
• Assist in data collection, cleaning, preprocessing, and feature engineering.
• Support the training, evaluation, and fine-tuning of machine learning models.
• Collaborate with senior engineers and researchers on AI/ML development tasks.
• Implement algorithms and develop software components related to AI/ML.
• Conduct research on new ML techniques and libraries.
• Assist in the creation of technical documentation and reports.
• Participate actively in code reviews and team discussions.
• Troubleshoot and debug software issues.
• Stay updated with the latest advancements in the field of machine learning.

• Recent graduate with a Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related quantitative field.
• Strong understanding of fundamental machine learning concepts and algorithms.
• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Familiarity with data manipulation tools (e.g., Pandas, NumPy).
• Excellent problem-solving and analytical skills.
• Strong programming and software development fundamentals.
• Good communication and teamwork skills.
• Ability to work independently and manage time effectively in a remote setting.
• Enthusiasm for AI and machine learning.