We’re currently seeking for an internship position in the Data Processing Developer Technology team. Would you enjoy researching parallel algorithms to accelerate AI and Data Processing workloads on advanced computer architectures? Do you find it rewarding to identify and eliminate...
This internship involves researching and developing GPU-accelerated techniques for deep learning, machine learning, and AI workloads. You will collaborate with experts to optimize complex algorithms, publish findings, and influence next-generation hardware and software design.
The Data Scientist role at SRT Marine Systems involves developing and evaluating ML models for maritime and security-based problems, such as detection, classification, and anomaly detection in time series and image/video data. You will collaborate with developers and engineers to integrate these models into user-facing features and build scalable data pipelines.
This role involves building and maintaining data pipelines, data warehouses, and data lakes to ensure data accuracy, accessibility, and security. You will work closely with data scientists to deploy machine learning models and collaborate with domain teams to create reusable patterns and automation for a new standalone payments business using Databricks and AWS.
This role involves hands-on data science work, contributing to the design, analysis, and build of data science solutions for real business problems. You will work on multiple projects, collaborate with engineers and analysts, and focus on production-focused initiatives with tangible impact.
As a Senior Data Scientist, you will lead technical consulting projects, develop and implement AI/ML solutions, and build client relationships across diverse industries, including defence. You will work on complex challenges, integrate code with software engineers, and support innovation and new techniques.
The Data Scientist will develop and implement machine learning models to solve business problems, analyse large datasets for actionable insights, and collaborate with technical and business stakeholders to deliver data-driven solutions. The role involves preparing, cleaning, and transforming data, as well as evaluating and monitoring models for accuracy and reliability.
This role involves building and maintaining scalable data pipelines, designing data models, and developing machine learning solutions to support AI initiatives and business intelligence. You will work closely with stakeholders to translate business challenges into technical solutions, using tools like Microsoft Fabric, Databricks, and PySpark.
This role involves designing and building scalable data pipelines using Databricks and Spark, developing robust ETL/ELT solutions, and supporting AI and machine learning initiatives. You will work closely with stakeholders to translate business requirements into technical solutions and maintain data models within modern lakehouse architectures.
This role involves designing and evolving a cloud-based data platform architecture, assessing new technologies, defining standards, and supporting data governance and AI readiness. You will work closely with engineering, analytics, and product teams to ensure data scalability and trustworthiness.
This role involves developing and deploying machine learning and NLP models for intelligence data, working closely with end users in a multi-disciplinary team. Responsibilities include pattern detection, data matching, anomaly spotting, and building production-ready data and ML pipelines.
This role involves designing and owning cloud-native data platforms for Defence, Government, and National Security clients. You'll work with big, messy, multi-source datasets, building scalable data lakes and pipelines on AWS or Azure, and collaborating closely with data scientists, software engineers, and architects.
As a Data Engineer, you will play a key role in migrating and consolidating existing data pipelines into a Snowflake-based platform, ensuring data quality and reliability. You will work closely with Data Scientists to support feature engineering and develop robust data models and transformation processes.
This role involves building and optimizing data pipelines to process and manage large volumes of data, enhancing the central data platform, and working closely with stakeholders to support investment decision-making. The successful candidate will have 3-6 years of experience, a strong background in SQL and Python, and direct experience in the hedge fund sector.
This role involves leading the end-to-end development of predictive models, starting with customer churn and complaint propensity, within a subscription-based business. The Data Scientist will define methodologies, build scalable production-ready solutions, and establish the foundation for the company's data science function. Emphasis is on hands-on modelling, commercial impact, and independent ownership of the full lifecycle from concept to deployment.
