1 to 25 of 32 Remote Feature Engineering Jobs

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

and methodologies to continually improve solution offerings. Provide expertise and guidance on AI best practices, contributing to the organization's AI strategy and innovation efforts. Conduct data analysis and feature engineering to prepare data for use in AI models, utilizing Azure Data Lake Develop robust testing and validation processes to ensure the accuracy and reliability of AI models … AI solutions, including Azure OpenAI Service, Azure Cognitive Services, and Azure Machine Learning. Familiarity with Azure Databricks is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large datasets, experience with Azure Data Factory, Azure SQL Database … Azure networking and security services tailored for AI applications. Excellent communication and teamwork skills, with experience working in agile development environments. Qualifications University degree in computer science or software engineering and/or 5+ years equivalent work experience within a cloud environment. Cloud Certifications desirable Qualifications such as the following desirable: Microsoft Azure AI Engineer Fundamentals/Associate Microsoft More ❯

and methodologies to continually improve solution offerings. Provide expertise and guidance on AI best practices, contributing to the organization's AI strategy and innovation efforts. Conduct data analysis and feature engineering to prepare data for use in AI models, utilizing Azure Data Lake Develop robust testing and validation processes to ensure the accuracy and reliability of AI models … AI solutions, including Azure OpenAI Service, Azure Cognitive Services, and Azure Machine Learning. Familiarity with Azure Databricks is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large datasets, experience with Azure Data Factory, Azure SQL Database … Azure networking and security services tailored for AI applications. Excellent communication and teamwork skills, with experience working in agile development environments. Qualifications University degree in computer science or software engineering and/or 5+ years equivalent work experience within a cloud environment. Cloud Certifications desirable Qualifications such as the following desirable: Microsoft Azure AI Engineer Fundamentals/Associate Microsoft More ❯

Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This position is within our decision sciences practice which focuses on delivering solutions via machine learning and statistical modelling. What you will do As a part of Aimpoint … Become a trusted advisor working with clients to design end-to-end analytical solutions Work independently to solve complex data science use-cases across various industries Design and develop feature engineering pipelines, build ML & AI infrastructure, deploy models, and orchestrate advanced analytical insights Write code in SQL, Python, and Spark following software engineering best practices Collaborate with … impact for your clients and do so through thoughtfulness, prioritization, and seeing a solution through from brainstorming to deployment. In particular you have these traits: Degree in Computer Science, Engineering, Mathematics, or equivalent experience. Experience with building high quality Data Science models to solve a client's business problems Experience with managing stakeholders and collaborating with customers Strong written More ❯

and visibility functionality. As a senior member of the team, you'll be self motivated and be able to take ownership of projects, collaborate closely with stakeholders across product, engineering, and business to deliver data science solutions. Responsibilities Work across and support a range of data use cases including analytics and data provisioning Lead the design, development, and deployment … models and advanced analytics solutions to support recommendation and insight to production use cases Apply statistical techniques to extract insights and support data-driven decision-making Work alongside data engineering in requirements for data pipelines and feature engineering Promote best practices in data science, model validation, documentation, and reproducibility Qualifications Experience Strong coding skills in Python, including More ❯

ll Bring: We are seeking a seasoned professional who is excited by the unique challenges of AI data. Qualifications What are we looking for? Must-Have Skills: Extensive Data Engineering Experience: Proven track record (3+ years) in designing, building, and maintaining large-scale data pipelines and data warehousing solutions. Cloud Platform Mastery: Expert-level proficiency with at least one … data technologies like Apache Spark, Kafka, and data orchestration tools such as Apache Airflow or Prefect. ML Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering, data validation, and dataset versioning. Vector Database Experience: Practical experience working with vector databases (e.g., Pinecone, Milvus, Chroma) for embedding storage and retrieval. Generative AI Familiarity: Understanding … TensorFlow for data preparation in an ML context. Experience with real-time data streaming architectures. Familiarity with containerization (Docker, Kubernetes). Master's or Ph.D. in Computer Science, Data Engineering, or a related quantitative field. Additional Information Starcom has fantastic benefits on offer to all of our employees. In addition to the classics,Pension,Life Assurance, Private Medical and More ❯

platforms (GCP preferred, AWS and Azure acceptable) Familiarity with Python ML packages such as PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas Strong SQL skills for data preparation and feature engineering Knowledge of MLOps principles, including automated retraining, monitoring, and deployment strategies Basic understanding of containerization and tools like Docker Nice-to-have skills: Experience with Google Cloud More ❯

Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & feature engineering * Understanding of & practical experience with implementing MLOps principals - including automated model retraining, monitoring & deployment strategies * Some knowledge of containerisation & use of tools like Docker & Docker Compose Nice More ❯

machine learning and deep learning models. Contribute to scalable and reusable data pipelines using modern ML workflows. Conduct experiments and benchmarking exercises to test model performance. Perform error analysis, feature importance, and other model diagnostics. Track and log training/testing outcomes to support reproducibility and model versioning. Engineering Contributions Help build and integrate AI-powered APIs, scripts … tools, and containerization (e.g., Docker) to maintain codebase quality. Applied AI Domains Work on projects involving Natural Language Processing (NLP), Computer Vision, Generative AI, or Recommendation Systems. Support annotation, feature engineering, and augmentation tasks where necessary. Write clear, well-organized documentation for code, models, datasets, and workflows. Participate in team meetings, sprint planning, and code reviews. Engage with … to reflect on progress, set learning goals, and track outcomes. Required Qualifications A Bachelor's or Master's degree (completed or ongoing) in Computer Science, Data Science, Mathematics, Software Engineering, or a related STEM field. Eligibility to enroll in a Level 6 or Level 7 AI/ML/Data Science apprenticeship programme. Core Skills & Competencies Technical Skills Programming More ❯

Domain: Automotive Job Type: Permanent/Contract Location: Onsite in West Midlands, UK/Remote The ideal candidate brings hands-on experience in machine learning model development, integration with engineering simulations, and practical application to propulsion system delivery. You will be responsible for creating advanced digital tools that accelerate and enhance the performance, accuracy, and efficiency of propulsion system … Python, including ML libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, etc. Expert Level in programming such as VBA, Python, JAVA and other coding tools. Familiarity with data processing, feature engineering, and model evaluation techniques. Soft Skills: Strong analytical and creative thinking skills to apply AI in complex engineering contexts. Excellent communication skills for cross-functional collaboration … and presenting technical results. Initiative-driven with a passion for innovation and digital transformation. Education: Bachelor's or Master's degree in Mechanical Engineering, Computer Science, Data Science, Mechatronics, or a related field. Additional certifications or training in AI/ML or Data Engineering are highly desirable What we offer (For Permanent) Competitive Salary in line with level More ❯

AWS and Databricks • Practical knowledge of tools such as MLflow, Delta Lake, and Apache Spark for pipeline development and model tracking • Experience architecting end-to-end ML solutions, including feature engineering, model training, deployment, and ongoing monitoring • Familiarity with data pipeline orchestration and a strong grasp of DevSecOps best practices in cloud-native environments • Hands-on experience with More ❯

and gain exposure to a wide range of tools, including cloud-based AI/ML platforms. What you'll do: Support development and optimisation of ML models through EDA, feature engineering, and testing Assist with data labelling, wrangling, validation, and governance Collaborate with stakeholders to deliver analytical insights and AI-driven solutions Use Python, SQL, and cloud-based More ❯

the organization. Essential Duties Understand business problems and conduct statistical analysis independently. Break down hard problems. Communicate effectively to senior stakeholders. Deliver value end-to-end. Self-serve data engineering and infrastructure as required. Make recommendations on best practice in terms of analysis, machine learning and data science. Have a transformative presence in the team. Develop and implement machine … learning models, including feature engineering, model design, training, and deployment. Perform data mining, exploration, and statistical analysis to uncover trends and actionable insights. Create data visualizations, reports, dashboards, and perform data audits. Leverage predictive models to optimize customer experiences and drive business outcomes. Create automated anomaly detection systems to monitor and ensure data quality and operational performance. Desired … Computer Science, or a related field. D. in a quantitative field such as Statistics, Computer Science, Mathematics, or Engineering. A "full stack" data scientist - with extensive expertise of data engineering, analysis and analytics, as well as machine learning. 6+ years of experience working in Data Science, preferably within a Software organization. Experience with financial fraud detection and prevention is More ❯

well as: Bachelor’s or master’s degree in computer science, Artificial Intelligence, Machine Learning, or a related field (desirable). Strong understanding of data structures, algorithms, and software engineering principles. Familiarity with data preprocessing, feature engineering, and model evaluation techniques. Familiarity with AI, machine learning, or blockchain technologies. Excellent communication, and problem-solving skills. Understanding of More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

at scale to help optimise product bidding and maximise profit across platforms like Google Shopping. Expect to work across the full ML lifecycle-from exploring large, messy datasets and engineering features, to evaluating models offline and running experiments to validate impact. At the same time, you'll build, deploy and monitor models in production: setting up retraining workflows, pipeline … clean, documented, well tested and reviewed code and have tooling and a culture to support this. This is a hands-on, high-impact role that blends research, experimentation and engineering, all tied to clear business outcomes. You'll collaborate closely with marketers, data analysts and engineers, and play a key part in shaping the future of how we scale … impact ad quality or model input 3+ years of experience building and deploying ML models in production Strong Python and SQL skills, with a solid understanding of data wrangling, feature engineering and model evaluation Deep understanding of the data science process-comfortable with exploratory analysis, statistical testing, and model comparison techniques Experience with structured prediction problems (e.g. regression More ❯

datasets (e.g. genomic sequences, patient records, imaging) Collaborate with bioinformaticians and clinical researchers to translate data into actionable insights Contribute to the development of internal tools for data preprocessing , feature engineering , and model evaluation Requirements: 3+ years of experience in data science or ML, ideally in biotech or healthcare Strong Python programming skills and experience with ML libraries More ❯

datasets (e.g. genomic sequences, patient records, imaging) Collaborate with bioinformaticians and clinical researchers to translate data into actionable insights Contribute to the development of internal tools for data preprocessing , feature engineering , and model evaluation Requirements: 3+ years of experience in data science or ML, ideally in biotech or healthcare Strong Python programming skills and experience with ML libraries More ❯

environment (AWS, GCP or Azure) Collaborate with data engineers, analysts, and product teams to translate business needs into AI-driven solutions Contribute to the development of data pipelines and feature engineering workflows Integrate models into production using APIs, batch jobs, or real-time systems Apply best practices around experimentation, evaluation, versioning, and monitoring Contribute to documentation, knowledge sharing More ❯

production-level solutions Troubleshoot and debug code Work with other teams to understand and solve business problems About you: Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine Learning Deployment: Familiarity with containerised deployment More ❯

happy - by continuously training and deploying machine learning models. We aim to make model deployments as easy and error-free as code deployments. Google's Best Practices for ML Engineering is our bible. Our models are trained to spot multiple types of fraud, using a variety of data sources and techniques in real time. The prediction pipelines are under … it's down to the Detection team to investigate why. The Detection team is core to Ravelin's success. They work in a deeply collaborative partnership with the Data Engineering team to design the data architecture and infrastructure that powers our ML systems. The Role We are looking for a Senior Machine Learning Engineer to join our Detection team. … Beyond just consuming data, you will take a leading role in defining how data is modeled, stored, and served for machine learning purposes, directly influencing the architecture of our feature generation pipelines and ensuring data quality throughout the ML lifecycle. You'll take strategic ownership over several aspects of our ML infrastructure and be empowered to introduce and champion More ❯