Data Solution Designer Data Science

Role / Job Title:Data Solution Designer Data ScienceWork Location:Norwich 3 Days (Flexible)Duration of Assignment:06 MonthsThe RoleThe 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.This role bridges business stakeholders, data engineering, data science, and IT architecture teams, ensuring solutions are production ready and aligned with enterprise standards.Your ResponsibilitiesSolution & Data Model Design1. Solution Design & ArchitectureDesign end to end data science solutions including data ingestion, feature engineering, model development, deployment, and monitoringDefine logical and physical architectures for analytics platforms, ML pipelines, and AI productsEnsure solutions are scalable, reusable, secure, and cost effectiveSelect appropriate ML/AI techniques (e.g., regression, classification, NLP, forecasting, clustering)2. Data & Analytics Engineering AlignmentWork closely with data engineers to define:Data models and schemasData quality rulesETL / ELT pipelinesDefine feature stores, training datasets, and inference pipelines3. Model Development & Deployment StrategyGuide data scientists on:Model selection and evaluation strategiesExperiment tracking and reproducibilityDesign MLOps frameworks for:CI/CD of ML modelsModel versioning and governanceMonitoring drift, accuracy, and bias4. Technology & Platform GovernanceDefine standards for:Programming languages and frameworksCloud vs on prem deploymentsSecurity, privacy, and complianceEnsure adherence to data governance, regulatory, and risk controls (especially in BFSI)5. Documentation & Best PracticesProduce:High level architecture diagramsLow level design documentsNon functional requirement specificationsEstablish best practices and reusable design patternsYour ProfileEssential Skills / Knowledge / ExperienceData Science & MLSupervised and unsupervised learningTime series, NLP, recommendation systems (as applicable)ProgrammingPython (NumPy, Pandas, Scikit learn)Optional: R, SQLData PlatformsRelational & NoSQL databasesBig data frameworks (Spark, Hive, Databricks)MLOps & DeploymentModel lifecycle managementCI/CD xjdpvnf pipelinesContainerization (Docker, Kubernetes desirable)Model packaging and REST APIsCloud & Tools (Any combination)AWS / Azure / GCP analytics and ML servicesMLflow, Azure ML, SageMaker, Vertex AIVersion control (Git)Domain & Soft SkillsStrong analytical and problem solving skillsAbility to explain complex data science concepts in simple business languageExperience working in Agile / Scrum environmentsStakeholder management and decision facilitationPreferred QualificationsBFSI domain experience (risk, fraud, AML, credit, customer analytics)Experience with regulatory data modelling and explainable AI (XAI)Exposure to GenAI, LLMs, and vector databasesDesirable Skills / Knowledge / ExperienceTOGAF or cloud architecture certifications

Created: 2026-03-23