At a Glance
- Tasks: Lead technical projects to modernise data capabilities and enhance governance.
- Company: Join a forward-thinking investment management firm with a focus on innovation.
- Benefits: Competitive salary, generous leave, pension scheme, and wellness support.
- Other info: Enjoy a supportive culture with opportunities for personal and professional growth.
- Why this job: Make a real impact in data strategy while developing your project management skills.
- Qualifications: Experience in data projects and strong stakeholder management skills required.
The predicted salary is between 60000 - 75000 £ per year.
In your role as Technology Workstream Lead you will make a meaningful and valued contribution from the outset. This role will provide a great opportunity to provide overall delivery management of the Technical platform for a complex Data Strategy & Architecture programme, ensuring the successful delivery of initiatives that modernise data capabilities, strengthen data governance and enable business value through data.
The role will oversee other Technical USS workstream leads, who are responsible for managing the design/architecture and delivery of internal platform components, along with third‑party delivery managers responsible for delivering the external technical platform. The role will work alongside the Business Workstream lead, who is responsible for business analysis and readiness (including UAT and training) and will provide end‑to‑end project management including planning, execution, delivery and transition to BAU.
Responsibilities
- Lead the planning, execution, delivery and closure of the Technical Workstream within the Data Strategy & Architecture programme
- Ensure scope, timelines and quality standards are met
- Translate strategic objectives into clear project plans, milestones and deliverables aligned to the overall data strategy plan and priorities
- Manage risks, issues and dependencies across the workstream, escalating where appropriate and ensuring timely mitigation and resolution
- Coordinate and direct cross‑functional teams across multiple departments, fostering collaboration between business stakeholders, SMEs and change teams
- Establish and maintain strong stakeholder relationships at all levels, ensuring alignment, engagement and effective communication
- Adhere to programme governance and reporting processes, providing timely and transparent updates on progress, challenges and outcomes
- Manage budgets, resources and third parties within the Technical Workstream to deliver value efficiently
- Adhere to wider change management standards within Investment Change & Systems, making use of best practices, standards and tools
- Contribute to the continuous improvement of the wider programme and Investment Change & Systems, sharing lessons learned and conducting knowledge transfer
Qualifications
Essential:
- Proven track record of delivering technical, data‑related projects in the investment management sector
- Experience working within larger data initiatives such as data strategy, data platforms, data governance or data architecture
- Excellent stakeholder management, communication and presentation skills, including excellent written and spoken English
- Strong knowledge of project management methodologies (e.g. Agile, Waterfall or hybrid approaches)
- Strong competency within the Microsoft Office suite of products (Project, SharePoint, Word, PowerPoint, Excel)
- Well organised with strong attention to detail
- Able to build and manage a successful, motivated and disciplined project team
Desirable:
- Knowledge of investment data terminology and concepts, e.g. securities, pricing, books of records
- Knowledge and experience of third‑party investment data solutions/providers
- Experience of Atlassian tools and plugins (e.g. Confluence, Jira, BigPicture)
Benefits
- Great starting salary
- Generous annual leave package
- Access to a high quality pension scheme provided through Universities Superannuation Scheme
- Supportive people policies (including enhanced occupational sickness pay and family friendly pay)
- Financial contributions towards your personal development to help you maintain your physical and mental well‑being
- Access to a range of health and wellbeing services, i.e. private healthcare, discounted gym membership
- Learning and development opportunities to develop your skills, knowledge and talent
- Employee Volunteer Day’s to support the communities where you work and live
- Cycle to Work Scheme
EEO Statement
USSIM is proud to be an equal opportunity employer. We strive to ensure our recruitment process is as flexible and inclusive as possible so we can attract diverse candidates and recruit the best talent.
Technology Workstream Lead employer: USS
As a Technology Workstream Lead, you will join a forward-thinking organisation that prioritises innovation and employee well-being. With a generous benefits package, including a high-quality pension scheme and extensive learning opportunities, the company fosters a supportive work culture that encourages personal and professional growth. Located in a vibrant area, you'll have access to health and wellness services, as well as community engagement initiatives, making it an excellent place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Technology Workstream Lead
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
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We think you need these skills to ace Technology Workstream Lead
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 USS, 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 USS. 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 USS
✨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 USS!
✨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.
