At a Glance
- Tasks: Lead data operations, ensuring high-quality delivery and coordination across teams.
- Company: Join Wayve, a pioneering tech company focused on innovation and collaboration.
- Benefits: Enjoy a competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on continuous improvement and career development.
- Why this job: Make a real impact by streamlining data processes and enhancing team efficiency.
- Qualifications: 3+ years in program management with strong stakeholder management skills.
The predicted salary is between 60000 - 80000 £ per year.
The role involves being the delivery engine behind data and annotation operations, turning a high-variance pipeline of requests into predictable, high-quality delivery. Responsibilities include:
- Intake & stakeholder alignment: Understand each ask, confirm it's complete, align on the goal and success criteria, and identify missing inputs before work starts.
- Estimation: Coordinate estimation with engineering and data science / ML, facilitate trade-offs, and push back on unrealistic asks.
- Scheduling & setup: Structure and sequence tickets, and coordinate external suppliers to set annotation work up for success.
- Execution, comms & issue management: Keep work moving with clear status updates, risk and issue tracking, blocker removal, a visible "path to green," and well-aligned escalations across internal teams and partners.
- Enable self-serve users: Onboard, support, and troubleshoot Wayve's internal self-serve users across the whole annotation tool chain.
- Supplier coordination: Own day-to-day coordination with external annotation suppliers - onboarding, label guides, task launch, QA, and delivery tracking.
- Continuous improvement: Improve intake, ticketing, and reporting (including automation) while owning the judgment, negotiation, and unblocking that can't be automated.
In order to set you up for success, we're looking for the following skills and experience:
- Essential: ~3+ years in program, delivery, or operations coordination (TPM, project / program coordinator, or similar).
- Strong stakeholder management: Create clarity from underspecified asks and stay neutral and constructive when priorities compete.
- Technically fluent: Comfortable working with engineers and data science / ML and reasoning about data and pipelines.
- Brings structure: Proactive risk and issue management; escalates early with clear options.
- Clear communicator: Keep many parties aligned with timely, tailored updates.
- Collaborative: Influence without authority and build trust across teams and suppliers.
- Growth mindset: Open to feedback and always improving how the work gets done.
- Systems thinking: Reason about how the parts of a complex system fit together.
- Product-minded: Focus on outcomes and the people your programs serve.
Desirable experience includes:
- Experience in data operations, annotation / labelling workflows, or external vendor / supplier management.
- Comfortable with Jira (or similar) and with workflow automation.
- Exposure to ML / data pipelines, autonomy, or robotics.
This is a full-time role based in our office in London or Leonberg, operating a hybrid working policy that combines time together in our offices and workshops with time spent working from home.
Technical Program Manager, Data Operations employer: Wayve
Wayve is an exceptional employer that fosters a dynamic and collaborative work culture, where innovation thrives through teamwork and open communication. As a Technical Program Manager in Data Operations, you'll benefit from a hybrid working policy that balances office collaboration in London or Leonberg with the flexibility of remote work, ensuring a supportive environment for personal and professional growth. With a strong emphasis on continuous improvement and a commitment to employee development, Wayve empowers you to make a meaningful impact while advancing your career in a cutting-edge field.
StudySmarter Expert Advice🤫
We think this is how you could land Technical Program Manager, Data Operations
✨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 Wayve!
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We think you need these skills to ace Technical Program Manager, Data Operations
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 Wayve, 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 Wayve. 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 Wayve
✨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 Wayve!
✨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.
