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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Architect - Data Science - **Company:** TESTQ Technologies - **Location:** Leicester, UK (Remote available) - **Experience:** Experienced - **Salary:** £42,400.0 - £54,900.0 - **Contract:** Temporary contract - **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, BigQuery, Computer Programming, Data Architecture, Information Engineering, Data Governance, Data Visualization, Data Warehousing, Distributed Computing Environment, Data Flow Control, Github, R (Programming Language), Apache Hadoop, Monitoring of Systems, Apache Hive, Python (Programming Language), PostgreSQL, Machine Learning, MongoDB, MySQL, NoSQL, NumPy, Oracle (Applications), Redis, Power BI, OpenAI, Cloud Services, Tensorflow, Azure Machine Learning, Scala (Programming Language), Shell Script, SQL Databases, Tableau (Software), Unstructured Data, Circleci, Pinecone, Scripting, Google Cloud, Pytorch, LangChain, Retrieval-Augmented Generation, Transfer Learning, Delivery Pipeline, Large Language Models, Snowflake, Apache Spark, Llamaindex, Generative AI, Keras, Langfuse — LLM Observability and Analytics Platform, Agentic-AI, Gitlab, Git, Pandas, Pgvector, Containerization, Data Lakes, Scikit Learn, Kubernetes, Information Technology, Apache Flink, Cassandra, HuggingFace, Data Analytics, Xgboost, Weaviate, Google Bigquery, Plotly, Apache Kafka, Milvus, Graphql, Machine Learning Operations, Api Design, Google Gemini, Terraform, Azure Synapse Analytics, Looker Analytics, Software Version Control, Data Pipelines, Docker, Jenkins, Amazon Redshift, Databricks - **Published:** October 2, 2026 - **Apply:** https://www.jobs.service.gov.uk/auth/sign-in?returnTo=%2Fjobs%2F6abe1b16dd2a3214b11c436e%2Fbefore-you-apply ## About the Role [The candidate must demonstrate these in all stages of assessment] * A bachelor's degree in Computer Science, Information Technology, or a related discipline. * 3 to 4 years of professional experience in Technical Architect - Data Science or equivalent roles. * Strong proficiency in programming and scripting languages such as Python, R, SQL, Java, Scala, and Shell scripting. * Adept at using data science and machine learning libraries including NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, XGBoost, and LightGBM for building and deploying advanced analytical models. * Hands-on experience with Generative AI and LLM tooling, including LangChain, LlamaIndex, Hugging Face Transformers, OpenAI/Azure OpenAI, AWS Bedrock, and vector databases such as Pinecone, Weaviate, Milvus, or pgvector for building RAG and agentic applications. * Solid understanding of data engineering and big data ecosystems, with hands-on experience using Apache Airflow, dbt, and Dagster for data workflow orchestration, and familiarity with Hadoop, Spark, Hive, Kafka, and Flink for distributed data processing. * Expertise in relational and NoSQL databases such as PostgreSQL, MySQL, Oracle, MongoDB, Cassandra, and Redis, along with experience managing data lakes and data warehouses such as Snowflake, Databricks (including Unity Catalog and Delta Lake), Amazon Redshift, Google BigQuery, and Azure Synapse. * Deep experience with cloud platforms - including AWS (S3, Glue, SageMaker, Bedrock, EMR, Lambda), Microsoft Azure (Data Lake, Synapse, Azure ML Studio, Azure OpenAI, Databricks), and Google Cloud Platform (BigQuery, Vertex AI, Gemini, Dataflow) - and the ability to design scalable, cloud-native data and AI solutions. * Proficiency in MLOps and LLMOps tooling such as MLflow, Kubeflow, DVC, TensorFlow Extended (TFX), and Weights & Biases to enable model lifecycle management, evaluation, and monitoring. * Knowledge of CI/CD pipelines using tools like Jenkins, GitHub Actions, Azure DevOps, or CircleCI, and experience with Infrastructure-as-Code (Terraform) plus containerization and orchestration through Docker, Kubernetes, and Helm. * Familiarity with model monitoring, evaluation, and AI governance tools such as Evidently AI, WhyLabs, Neptune.ai, Arize AI, or Langfuse. * Expertise in data visualization and business intelligence tools including Power BI, Tableau, Looker, Superset, Plotly, and Dash for translating analytical and AI-driven insights into actionable business intelligence. * Strong understanding of API design and integration (REST, GraphQL, gRPC), version control systems (Git, GitLab), and data security and compliance frameworks such as GDPR, HIPAA, SOC 2, and emerging AI regulation (e.g., EU AI Act). Qualifications: Bachelor's degree or above in the UK or equivalent. ## Description The Technical Architect - Data Science is responsible for designing, developing, and implementing end-to-end data, analytics, and AI solutions, including Generative AI and LLM-based systems. This role bridges data engineering, data science, and architecture by defining scalable frameworks, guiding model deployment, and ensuring optimal use of cloud, big data, and modern AI technologies. Job Description (Main Duties and Responsibilities) * Design and architect end-to-end data science, machine learning, and Generative AI solutions aligned with enterprise strategy. * Define scalable data architectures for ingestion, processing, storage, and analytics across structured and unstructured data. * Lead the design of machine learning pipelines, LLM/RAG application architectures, model deployment frameworks, and MLOps/LLMOps solutions. * Collaborate with data scientists, ML engineers, and analysts to operationalize ML and GenAI models in production. * Evaluate and recommend tools, frameworks, and best practices for data science, AI, and Generative AI initiatives. * Ensure compliance with data governance, security, privacy, and responsible AI standards. * Provide technical leadership and mentorship to the data science and engineering teams. * Optimize cloud and on-premises data architectures for performance, cost, and scalability. * Drive innovation through proof-of-concepts (POCs) and pilot implementations of emerging AI/ML and GenAI technologies, including LLM fine-tuning and agentic workflows.