At a Glance
- Tasks: Manage and coordinate exciting data projects in the AI space.
- Company: Join a forward-thinking company at the forefront of AI technology.
- Benefits: Flexible working hours, competitive pay, and opportunities for growth.
- Other info: Dynamic team environment with a focus on collaboration and creativity.
- Why this job: Be part of innovative projects that shape the future of AI.
- Qualifications: Strong communication skills and experience with project management tools.
The predicted salary is between 50000 - 70000 £ per year.
We are looking for an Agent Environment Data Project Manager to support the daily execution and coordination of Agent environment data projects.
This role will work closely with large language model companies, research and engineering teams, domain experts, and external vendors to ensure project requirements, documentation, timelines, deliveries, and quality feedback are managed smoothly and efficiently.
Responsibilities
- Manage daily operations of Agent environment data projects, including project documentation, requirement notes, annotation guidelines, and progress reports.
- Communicate with large language model companies to understand project requirements, clarify expectations, and support delivery alignment.
- Track project schedules, task assignments, delivery milestones, and quality feedback to ensure projects move forward on time.
- Coordinate research, engineering, and expert teams to support task allocation, execution, review, and issue resolution.
- Identify and escalate project risks, blockers, requirement changes, and quality issues in a timely manner.
- Support vendor portal operations, including task creation, data upload and download, status tracking, and result consolidation.
- Maintain clear project records, status updates, and workflow documentation using collaboration and project management tools.
Requirements
- Strong documentation skills, with the ability to write clear project documents, requirements, annotation guidelines, and progress updates.
- Good communication and coordination skills, with the ability to work across clients, internal teams, experts, and vendors.
- Strong execution ability, attention to detail, and sense of responsibility.
- Proficiency with spreadsheets, documents, and project management tools such as Notion, Google Workspace, and Slack.
- Ability to track multiple tasks, follow up on details, and keep stakeholders updated on progress and risks.
- Experience with data annotation, vendor collaboration, AI data projects, or LLM/Agent-related projects is preferred.
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StudySmarter Expert Advice🤫
We think this is how you could land Agent Environment Data Project Manager
✨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 Eigent AI!
✨Show Off Your Projects
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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 Eigent AI.
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We think you need these skills to ace Agent Environment Data Project Manager
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 Eigent AI, 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 Eigent AI. 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 Eigent AI
✨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 Eigent AI!
✨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.
