Technical Architect - Data Science

Reference: TQ2526_2133_494

Vacancy: 1

Job title: Technical Architect – Data Science

Location: Leicester

Job Purpose

TESTQ Technologies is an IT services and solutions company whose offerings span a variety of industry sectors with strong technical, domain, and process expertise, helping clients grow their businesses and decrease operational costs on a continuous basis in an ever-changing business environment.

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.

Key Skills, Qualifications and Experience Needed

[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.

Salary: GBP 42,400 to GBP 54,900 per annum

Published Date: 01 October2026

Closing Date: 30 October 2026

Evaluation: CV Review, Technical Test, Personal and Technical Interview, and References

Job Type: Full-time, Permanent [Part time and Fixed Term option is available]

Pay: £42,400.00-£54,900.00 per year

Work Location: Remote