At a Glance
- Tasks: Tackle complex machine learning challenges and develop high-quality ML models.
- Company: Obsidian, a leader in advanced machine learning solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Ideal for those with a Master’s or PhD in a relevant field.
- Why this job: Join a team pushing the boundaries of machine learning and make a real impact.
- Qualifications: 2+ years of ML experience and strong Python skills required.
The predicted salary is between 70000 - 90000 £ per year.
Obsidian is hiring experienced Machine Learning Engineers and Applied ML Researchers to tackle complex machine learning challenges. This role requires hands-on modeling expertise and the ability to develop high-quality solutions across various domains.
The ideal candidate will have 2+ years of experience in developing ML models and a strong proficiency in Python, along with a Master’s or PhD in a relevant field. Apply now to contribute to advanced machine learning projects!
Applied ML Researcher: End-to-End Models employer: Obsidian
At Obsidian, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to excel in their roles. As an Applied ML Researcher, you will have access to cutting-edge technology and resources, along with ample opportunities for professional growth and development. Located in a vibrant tech hub, we offer a dynamic environment where your contributions will directly impact advanced machine learning projects, making your work both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Applied ML Researcher: End-to-End Models
✨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 Obsidian!
✨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 Applied ML Researcher: End-to-End Models at Obsidian.
✨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 Obsidian.
✨Apply Directly through Our Website
When you find a suitable opening like Applied ML Researcher: End-to-End Models at Obsidian, 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 Applied ML Researcher: End-to-End Models
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 Obsidian, 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 Obsidian. 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 Obsidian
✨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 Obsidian!
✨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.
