At a Glance
- Tasks: Lead the design and development of data-driven decision models for workforce planning.
- Company: Bounteous, a top digital transformation consultancy with a global presence.
- Benefits: Competitive salary, diverse projects, and opportunities for professional growth.
- Other info: Join a diverse team committed to innovation and equal opportunity.
- Why this job: Make a real impact by shaping data strategies that drive business success.
- Qualifications: 5+ years in data science, strong analytical skills, and proficiency in SQL and Python.
The predicted salary is between 76662 - 93698 £ per year.
Bounteous is a premier end-to-end digital transformation consultancy dedicated to partnering with ambitious brands to create digital solutions for today’s complex challenges and tomorrow’s opportunities. With uncompromising standards for technical and domain expertise, we deliver innovative and strategic solutions in Strategy, Analytics, Digital Engineering, Cloud, Data & AI, Experience Design, and Marketing.
Position Summary: This role will be key to helping our divisional leadership to make 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.
Key Responsibilities:- Design & Architecture: Lead design for decision support model from formation through to deployment. Define model framework that balances predictive accuracy with interoperability and usability.
- Data Integration & Engineering: Partner with other teams responsible for datasets required to be leveraged so it can be sourced, cleansed, and prepared into a structured format, where possible.
- Model Development: 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: Translate business requirements into analytic frameworks and technical solutions. Work closely with business stakeholders to ensure the model aligns with strategic goals and operational needs.
- 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.
- Experience: Minimum of 5 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.).
- Data Modelling: Ability to build a methodology with statistical techniques and then scale and automate.
- Industry Expertise: Demonstrated experience across diverse sectors including Banking, Insurance, and Consultancy, focusing on Data Analytics and Data Insights.
- Stakeholder Engagement: Adept at translating analytical findings into actionable insights for various stakeholders, ensuring stakeholder centric outcomes.
- Project Management: Proficient in managing end-to-end analytics projects, leading initiatives to explore customer journeys, and data to drive business decisions.
- Technical Proficiency: 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.
Working knowledge of Snowflake Cortex. Some experience with Power BI. Need to create agents in Copilot.
Bounteous is proud to be an equal opportunity employer. Bounteous does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, national origin, veteran status, or any other status protected under federal, state, or local law. Bounteous is willing to sponsor eligible candidates for employment visas.
Senior Data Engineer in Glasgow employer: Bounteous
Bounteous is an exceptional employer that fosters a collaborative and innovative work culture, particularly in the dynamic EMEA region. Employees benefit from extensive professional development opportunities and are encouraged to take on challenging projects that drive personal and career growth. With a focus on teamwork and client success, Bounteous offers a rewarding environment for those looking to make a significant impact in the capital markets sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in Glasgow
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Bounteous!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Bounteous.
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We think you need these skills to ace Senior Data Engineer in Glasgow
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Bounteous, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Bounteous. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Bounteous
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Bounteous!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
