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  "job_description": "Role / Job Title: Data Solution Designer Data Science\n\nWork Location: Norwich 3 Days (Flexible)\n\nDuration of Assignment: 06 Months\n\nThe Role\n\nThe Data Solution Designer Data Science is responsible for designing end to end data science and advanced analytics solutions that translate complex business problems into scalable, secure, and high performance data products.\n\nThis role bridges business stakeholders, data engineering, data science, and IT architecture teams, ensuring solutions are production ready and aligned with enterprise standards.\n\nYour Responsibilities\n\nSolution & Data Model Design\n\n1. Solution Design & Architecture\n\nDesign end to end data science solutions including data ingestion, feature engineering, model development, deployment, and monitoring\nDefine logical and physical architectures for analytics platforms, ML pipelines, and AI products\nEnsure solutions are scalable, reusable, secure, and cost effective\nSelect appropriate ML/AI techniques (e.g., regression, classification, NLP, forecasting, clustering)\n2. Data & Analytics Engineering Alignment\n\nWork closely with data engineers to define:\n\nData models and schemas\nData quality rules\nETL / ELT pipelines\n\nDefine feature stores, training datasets, and inference pipelines\n3. Model Development & Deployment Strategy\n\nGuide data scientists on:\n\nModel selection and evaluation strategies\nExperiment tracking and reproducibility\n\nDesign MLOps frameworks for:\n\nCI/CD of ML models\nModel versioning and governance\nMonitoring drift, accuracy, and bias\n\n4. Technology & Platform Governance\n\nDefine standards for:\n\nProgramming languages and frameworks\nCloud vs on prem deployments\nSecurity, privacy, and compliance\n\nEnsure adherence to data governance, regulatory, and risk controls (especially in BFSI)\n5. Documentation & Best Practices\n\nProduce:\n\nHigh level architecture diagrams\nLow level design documents\nNon functional requirement specifications\n\nEstablish best practices and reusable design patterns\nYour Profile\n\nEssential Skills / Knowledge / Experience\n\nData Science & ML\n\nSupervised and unsupervised learning\nTime series, NLP, recommendation systems (as applicable)\nProgramming\n\nPython (NumPy, Pandas, Scikit learn)\nOptional: R, SQL\nData Platforms\n\nRelational & NoSQL databases\nBig data frameworks (Spark, Hive, Databricks)\nMLOps & Deployment\n\nModel lifecycle management\nCI/CD pipelines\nContainerization (Docker, Kubernetes desirable)\nModel packaging and REST APIs\nCloud & Tools (Any combination)\n\nAWS / Azure / GCP analytics and ML services\nMLflow, Azure ML, SageMaker, Vertex AI\nVersion control (Git)\nDomain & Soft Skills\n\nStrong analytical and problem solving skills\nAbility to explain complex data science concepts in simple business language\nExperience working in Agile / Scrum environments\nStakeholder management and decision facilitation\nPreferred Qualifications\n\nBFSI domain experience (risk, fraud, AML, credit, customer analytics)\nExperience with regulatory data modelling and explainable AI (XAI)\nExposure to GenAI, LLMs, and vector databases\nDesirable Skills / Knowledge / Experience\n\nTOGAF or cloud architecture certifications\n\nTPBN1_UKTJ",
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  "job_posted_at_datetime_utc": "2026-03-24T00:00:00.000Z"
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