Alexander Ash Consulting

Developer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Developer in London, with a contract length of "unknown" and a pay rate of "unknown." Key skills include Python, ETL/ELT experience, and data governance. Financial industry experience is desirable. On-site work required.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
Unknown
-
🗓️ - Date
November 11, 2025
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
London Area, United Kingdom
-
🧠 - Skills detailed
#C++ #Deployment #ML (Machine Learning) #Data Science #Pandas #C# #Programming #Scala #AI (Artificial Intelligence) #Data Governance #TensorFlow #Java #Python #PyTorch #"ETL (Extract #Transform #Load)" #Automation #NumPy #Data Pipeline
Role description
Developer – London Overview We are seeking a Developer to help modernise core business processes through data-driven and AI-enabled solutions. The role focuses on building scalable systems that enhance automation, analytics, and decision-making across key business areas. Key Responsibilities: • Design and develop data and analytics platforms supporting multiple teams. • Collaborate with AI engineers, data scientists, and business stakeholders to enhance research and operational systems. • Build and maintain robust data pipelines for ingestion, transformation, and validation. • Contribute to the design and deployment of AI/ML models and data-driven tools. • Drive best practices in data governance and scalable software design. Required Skills & Experience: • Strong programming expertise in Python ideally - NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch • Experience developing ETL/ELT pipelines and working with structured/unstructured data. • Solid understanding of data structures, algorithms, and modern software engineering. • Excellent communication and collaboration skills. Desirable Skills: • Knowledge of C++, Java, or C#. • Exposure to MLOps, distributed systems, or financial data environments. • Understanding of financial products and data workflows.