18 of 18 Feature Engineering Jobs in the South East

experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders. This is not a heavy Data Engineering or MLOps … analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability to craft interpretable, business-relevant features Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where ...

experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders. This is not a heavy Data Engineering or MLOps … analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability to craft interpretable, business-relevant features Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where ...

experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders. This is not a heavy Data Engineering or MLOps … analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability to craft interpretable, business-relevant features Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where ...

experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders. This is not a heavy Data Engineering or MLOps … analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability to craft interpretable, business-relevant features Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where ...

experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders. This is not a heavy Data Engineering or MLOps … analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability to craft interpretable, business-relevant features Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where ...

experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders. This is not a heavy Data Engineering or MLOps … analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability to craft interpretable, business-relevant features Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where ...

experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders. This is not a heavy Data Engineering or MLOps … analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability to craft interpretable, business-relevant features Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where ...

experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders. This is not a heavy Data Engineering or MLOps … analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability to craft interpretable, business-relevant features Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where ...

building the future of population health management. As a Senior Machine Learning Engineer, you will sit at the intersection of data science, platform engineering, and production systems. Your mission is to design and operate the foundations that allow ML, analytics, and agentic AI systems to move safely and reliably … from experimentation into regulated healthcare production environments on Google Cloud Platform. You will be the primary interface between Data Science and Platform Engineering, enabling rapid iteration while enforcing production and compliance standards. Responsibilities Design and implement Onsera's agentic AI platform – architect LLM/agent framework selection, standardized patterns ...

across the business. They are looking for a Senior AI Engineer to lead the delivery of end-to-end AI products, working across software engineering, machine learning, and LLM-based systems. This is a hands-on role focused on shipping real solutions into production that directly impact customers, teams … commercial outcomes. The RoleYou will join a cross-functional AI function working at the intersection of software engineering, data, and machine learning. Your focus will be on turning business problems into production-ready AI systems, from early discovery through to deployment, monitoring, and continuous improvement. You will work closely ...

Drive experimentation frameworks, hypothesis testing, model validation, and statistical rigor Ensure robustness, generalisation, bias mitigation, and explainability in deployed models Provide technical direction on feature engineering strategies and model performance enhancement Collaborate with engineering teams to transition models into scalable production systems Mentor data scientists and uphold … 8+ years of hands-on experience in machine learning and data science Advanced degree (Master's or PhD preferred) in Computer Science, Statistics, Mathematics, Engineering, or related quantitative discipline Proven experience building and deploying advanced ML and deep learning models in enterprise environments Deep understanding of algorithm selection, model ...

clients. As a senior leader, you will interact frequently with customers, provide expert opinions, and contribute to HCL's strategic vision. Key Responsibilities Technical & Engineering Leadership • Design and implement AI and cloud architectures, integrating GenAI technologies to enhance functionality and scalability. • Lead architectural discussions with clients, providing expert guidance … Skills & Experience • Deep knowledge of machine learning operations (MLOps) and experience in deploying, monitoring, and maintaining AI models in production environments. • Proficiency in data engineering for AI, including data preprocessing, feature engineering, and pipeline creation. • Expertise in AI model fine-tuning and evaluation, with a focus ...

adapted across multiple operational entities globally. Key Responsibilities Design and implement predictive and prescriptive models to optimize MRO operations. Perform exploratory data analysis, feature engineering, and model validation. Collaborate with data engineering teams to ensure high-quality, production-ready datasets. Communicate findings and recommendations to senior business ...

cloud and on-prem data platforms , automation, and emerging AI-driven capabilities, and is specifically suited to candidates with strong, hands-on data engineering experience , particularly in building, operating, and optimising complex data pipelines, data models, and integration workflows at scale. Role Overview and Responsibilities As a Data & Automation … delivery processes using technologies such as Azure Data Factory, Databricks, SSIS, and SQL . Reducing manual interventions through automation and standardisation , including data preparation, feature engineering, and training-data pipelines. Preparing data models and datasets (DWH/Lakehouse) to support business intelligence, analytics, and operational reporting. Monitoring ...

optimisation project. You will design and implement predictive and prescriptive models for Maintenance, Repair, Overhaul AI Solutions. Performing exploratory data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modelling. Communicate findings and recommendations to business stakeholders. Continuously improve models based on feedback and operational ...

proof-of-concept development using Databricks notebooks, analytical outputs and machine learning techniques to validate product concepts Own technical product definition, including data structures, feature sets, scoring methodologies, model architectures and delivery formats in collaboration with the Product Team Define and monitor technical success metrics (data coverage, refresh latency … needs into technical product requirements Support rapid prototyping and proof-of-concept development using Databricks notebooks and analytics outputs Define product-level data structures, feature sets, scoring outputs and delivery formats in collaboration with the Product Team Product Launch & Performance responsibilities: Define technical success metrics (data coverage, refresh latency ...

compute performance. Deploy pipelines using CI/CD and IaC. Deliver curated datasets and semantic layers for BI, analytics, and ML. Support ML feature engineering and model delivery. Define scalable data architecture patterns and integration designs (ingestion, storage, transformation, analytics). Develop and maintain conceptual, logical, and physical … support scalability and strategic needs. Personal Requirements: 3–5+ years’ experience with Microsoft SQL Server (2016+) and SSIS in production environments. Strong SQL Server engineering: advanced T-SQL, indexing, performance tuning, execution plans, statistics, partitioning, tempdb optimisation. Proven experience with ETL/ELT development and design patterns (incremental loads ...

Forum, Metro Ethernet Forum, IETF, GSMA, Open Broadband etc. Working knowledge of classical AI and machine learning techniques, including supervised and unsupervised learning, feature engineering, model training, evaluation and deployment. Working knowledge of next‐generation AI approaches, including generative AI and agentic systems, such as large language models ...