1 to 25 of 31 Feature Engineering Jobs in the South East

analytics while collaborating with cross-functional teams as part of the BTS Data & Analytics team. You will work closely with key stakeholders in Engineering, Product, GTM, and other groups to help build scalable data solutions that support key metrics, reporting, and insights. You will assist in ensuring teams have … learning and AI model development, ensuring datasets are clean, well-structured, and readily usable by Data Science teams. Support the integration and management of feature engineering processes and model outputs into Foundry's data ecosystem, helping enable scalable deployment and monitoring of AI/ML solutions ...

Responsibilities Develop, train, and evaluate machine learning models to solve real-world business problems. Support the full ML lifecycle—from data exploration and feature engineering to deployment and monitoring. Work with large datasets using modern data tooling and cloud platforms. Implement scalable ML pipelines and contribute to automation … initiatives. Collaborate with cross-functional teams to translate client requirements into technical solutions. Stay updated with the latest advancements in ML, AI, and data engineering practices. About You A degree (BSc, MSc, or PhD) in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related STEM field. Strong ...

with data engineers and AI engineers on interfaces and SLAs. Required Skills & Experience Python (pandas, NumPy, scikit-learn; PyTorch/TF a plus). Feature engineering, data quality validation, model training and optimisation. MLOps: experiment tracking (e.g., MLflow), model registry, CI/CD for ML. Serving and orchestration … monitoring for drift/perf. Nice to Have Cost/performance optimisation on AWS; GPU scheduling; quantisation/distillation. Experience working within Financial Services engineering standards and governance. IND_PC3 Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy. ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

ability to gut them and work with them past just surface-level functionality. Experience with the full model development lifecycle, from data preprocessing and feature engineering to model validation. Degree in Computer Science, Machine Learning, Computational Chemistry, or equivalent industry experience. Nice To Haves Prior experience in computational ...

ability to gut them and work with them past just surface-level functionality. Experience with the full model development lifecycle, from data preprocessing and feature engineering to model validation. Degree in Computer Science, Machine Learning, Computational Chemistry, or equivalent industry experience. Nice To Haves Prior experience in computational ...

experience (professional or academic) applying analytics to solve real-world business problems. End-to-End Data Science: Practical knowledge across the full lifecycle—from feature engineering and model design to validation, deployment, and monitoring. Technical Proficiency: Fluency in Python, SQL, or similar languages, and experience with deep learning ...

frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. •Design and implement ML pipelines on Azure Machine Learning. •Own end-to-end model lifecycle: data ingestion, feature engineering ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

linked data science solutions. Working closely with data engineers to define data requirements and pipelines. Performing exploratory data analysis and recreating key business KPIs. Feature engineering in collaboration with machine learning engineers, ensuring production-ready standards. Developing, deploying and maintaining machine learning models. Evaluating project impact through experimentation ...

Qualifications and Experience PhD with at least 2 years of relevant experience, or MSc with at least 5 years of relevant experience, in biomedical engineering, health data science, machine learning, or a closely related field Strong understanding of cardiovascular diseases, clinical risk factors, and healthcare workflows Proven experience working … with real world healthcare data, including EHRs and wearable devices Expertise in handling missing data, outliers, and feature engineering in medical datasets Strong experience in time series analysis for physiological signals such as ECG or PPG Proficiency in Python for data analysis, hypothesis testing, and machine learning Experience ...

Qualifications and Experience PhD with at least 2 years of relevant experience, or MSc with at least 5 years of relevant experience, in biomedical engineering, health data science, machine learning, or a closely related field Strong understanding of cardiovascular diseases, clinical risk factors, and healthcare workflows Proven experience working … with real world healthcare data, including EHRs and wearable devices Expertise in handling missing data, outliers, and feature engineering in medical datasets Strong experience in time series analysis for physiological signals such as ECG or PPG Proficiency in Python for data analysis, hypothesis testing, and machine learning Experience ...

extensive work experience in the related field. Good understanding of cardiovascular diseases, risk factors and clinical workflows. Expertise in handling missing data, outliers and feature engineering. Experience in processing Health data from various sources (EHR, Wearables) and formats (e.g., HL7/FHIR, CSV, PDF, PNG, JPEG). Skilled ...

extensive work experience in the related field. Good understanding of cardiovascular diseases, risk factors and clinical workflows. Expertise in handling missing data, outliers and feature engineering. Experience in processing Health data from various sources (EHR, Wearables) and formats (e.g., HL7/FHIR, CSV, PDF, PNG, JPEG). Skilled ...