Senior Engineer, Data Engineering

4 weeks ago

Glasgow, United Kingdom Bounteous Full time

Senior Data Architect/Engineer Location : Glasgow, UK
This role will be key to helping our divisional leadership to making informed, data-driven decisions by developing a sophisticated, scalable and explainable decision model to aid workforce planning.
The ideal candidate will have deep expertise in data science, analytics and systems thinking, with a proven ability to work across different businesses. This is a high-impact role with the work output to be visible at the executive level.

Lead design for decision support model from formation through to deployment. Data Integration & Engineering : Apply statistical, machine learning or optimization techniques to develop a robust decision support system. Simulate scenarios, perform sensitivity analysis, and create “what-if” tools for stakeholders.
Business Analysis : Data Visualisation & Communication : Build dashboards, reports or interactive tools that clearly communicate model outputs and decision recommendations for executive levels.
Governance & Monitoring : align with governance practices including model risk management, validation, versioning, performance tracking and recalibration. Establish KPIs to measure the impact of the model on decision quality and business outcomes.

Data Modelling : Demonstrated experience across diverse sectors including Banking, Insurance, and Consultancy, focusing on Data Analytics and Data Insights.
Project Management : Proficient in managing end- to- end analytics projects, leading initiatives to explore customer journeys, and data to drive business decisions.
Skilled in SQL, Google Cloud Platform Big Query, Adobe Analytics, Tableau, Power BI, and Python, delivering data- driven recommendations and ensuring data quality in projects.
Commercial Analytics : Engaged in projects to understand impact on revenue, automated reporting, and improved efficiency using SQL, SAS, and Alteryx.
Data Quality and Governance : Ensured compliance with regulatory guidelines and addressed data gaps.
Regulatory Compliance and Reporting : Supported creation of dashboards & reporting, liaising with stakeholders and managing ad hoc MI requests.
Project Exposure: Performed profiling and trend analysis, analysis of large complex datasets to support decision- making, A/B testing, measurement of impact on commercial outcomes, impact analysis, performance analysis, identification of remediation issues involving data.

Experience: Minimum of 5 - 7 years of experience in data science, analytics, operational research or a related field.
Advanced degree in a quantitative field (e.g. Data Science, Engineering, Mathematics, etc.)

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