At a Glance
- Tasks: Own synthetic data pipelines and design evaluations for AI improvements.
- Company: Harvey, a pioneering company in professional services with frontier AI.
- Benefits: Competitive salary, flexible work options, and opportunities for growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Join a high-performing team and make a real impact in AI development.
- Qualifications: Experience in data engineering and a passion for machine learning.
The predicted salary is between 63000 - 77000 £ per year.
Harvey is shaping the future of professional services with frontier AI.
As a Member of Technical Staff, Data & Evals, you’ll own synthetic data pipelines, evaluation design, and the training signals that turn expert feedback into measurable improvements.
You’ll join a small, high‑bar team of engineers and researchers, work closely with legal domain experts, and build data systems that scale post‑training and benchmarking across complex workflows.
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Data & Evaluation Engineer - ML Benchmarking employer: Harvey
At Harvey, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and personal growth. Our London office is at the forefront of transforming professional services, providing employees with unparalleled opportunities to make a significant impact while working alongside a passionate team. With a commitment to excellence and a focus on employee development, we ensure that every team member can thrive in their career journey.
StudySmarter Expert Advice🤫
We think this is how you could land Data & Evaluation Engineer - ML Benchmarking
✨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 Harvey!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data & Evaluation Engineer - ML Benchmarking at Harvey.
✨Leverage Professional Networks
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 Harvey.
✨Apply Directly through Our Website
When you find a suitable opening like Data & Evaluation Engineer - ML Benchmarking at Harvey, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data & Evaluation Engineer - ML Benchmarking
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 Harvey, 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 Harvey. 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 Harvey
✨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 Harvey!
✨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.
