11 of 11 Permanent Use Case Jobs in Manchester

teams. The Role Build and fine tune LLMs and NLP models for analytics and conversational products. Apply mathematical and quantitative thinking to financial use cases. Develop ML pipelines, model evaluation processes, and production ready code. Work with engineers to deploy models in AWS. Support and guide mid level ...

from on-prem SQL Server into AWS, contributing to the design of lakehouse and data warehousing solutions that support high-transactional, high-volume use cases. Alongside delivery, you'll help raise standards across the data platform, contributing to shared tooling, best practice, and mentoring more junior engineers where ...

data supports business and product outcomes Comfortable collaborating across Data, Engineering, and Product in a fast moving environment Exposure to ML or analytics use cases, including preparing data for modelling or experimentation, is highly beneficial What They Offer Clear scope for progression as the data platform and team ...

manage data ingestion pipelines that feed into their cloud data warehouse. Build and maintain pipelines that prepare data for machine learning and analytics use cases. Restructure/improve existing datasets to ensure they are reliable, performant and ML-ready. Work closely with Data Science and Platform Engineering ...

stack Proven experience with GCP, BigQuery, dbt, and ELT tools such as Fivetran or similar Solid data modelling capability for analytics and reporting use cases Hands-on experience with infrastructure as code, particularly Terraform Comfortable working in scaling environments with evolving data maturity Able to communicate clearly with ...

programme. You'll be working on the design and development of robust data processing systems that underpin analytics, data science and machine learning use cases. This role offers the chance to work on complex data platforms while collaborating with data scientists, engineers and stakeholders in a highly skilled ...

data platform evolves, strengthening analytics capabilities and maturing data engineering practices. You will ensure the business can continue to scale its use of data without compromising quality, governance or performance. Data Team Lead Skills Proven experience leading and developing high-performing, collaborative data engineering teams Strong background working … relational or semi-structured data sources Understanding of modern data modelling for analytics and reporting Awareness of machine learning workflows or advanced analytics use cases Understanding of networking, security and access control within AWS or Azure Awareness of data governance and regulatory requirements (including GDPR) Experience & Behaviours Significant ...

product strategy into detailed requirements for prototyping and final development by engineering teams Create product strategy documents that describe business cases, high-level use cases, technical requirements, revenue, and ROI Analyze market data to develop sales strategies, and define product objectives for effective marketing communications Collaborate closely with ...

open-source software where appropriate. 3 Month Plan: Develop a working understanding of the product, federated training setup, and key life-sciences modelling use cases. Reproduce and extend at least one existing modelling pipeline to establish a baseline privacy and attack-surface assessment. Contribute to privacy analysis ...

open-source software where appropriate. 3 Month Plan: Develop a working understanding of the product, federated training setup, and key life-sciences modelling use cases. Reproduce and extend at least one existing modelling pipeline to establish a baseline privacy and attack-surface assessment. Contribute to privacy analysis ...

Tesco, Sainsbury's, O2, Halifax, AA, Saga and Lloyds Bank to list a few. Role overview As a Senior Data Scientist, you will use your advanced analytical skills to: Lead the development of cutting-edge, bespoke machine learning predictive models, including risk pricing and classification and regression models … bespoke modelling. Such work would include risk classification, such as area or vehicle classification, as well as predictive models for other business use cases such as conversion, retention or price optimisation Prototype ML solutions before handing to the ML team for implementation Conduct more advanced yet focused research ...