Senior AI & Data Engineer β€” Hybrid, Mentoring & Paid Leave

Senior AI & Data Engineer β€” Hybrid, Mentoring & Paid Leave

Full-Time 59400 - 72600 Β£ / year (est.) Hybrid
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At a Glance

  • Tasks: Own the analysis engine, shape narratives, and build scalable data pipelines.
  • Company: Dablam, a forward-thinking company with a focus on innovation.
  • Benefits: Hybrid work model, mentoring opportunities, and paid leave.
  • Other info: Join a dynamic team in London with great career growth potential.
  • Why this job: Make a real impact by solving complex measurement problems in a collaborative team.
  • Qualifications: Experience in analytics engineering and strong communication skills.

The predicted salary is between 59400 - 72600 Β£ per year.

Dablam is seeking a skilled Analytics Engineer to own the analysis engine behind Orion, shaping how narratives, scores and sources are produced in our platform.

You will be responsible for ensuring reproducible clustering, narratives over time, and scalable data pipelines, partnering with the CEO and a Full Stack Engineer.

You will tackle hard measurement problems, explain methods to non-technical colleagues, and ship end-to-end in a small team, with hybrid work in London.

Senior AI & Data Engineer β€” Hybrid, Mentoring & Paid Leave employer: Dablam

Dablam offers a dynamic work environment where employees can engage in challenging projects that shape the future of reputation intelligence. The company promotes professional growth through mentorship and collaboration with experienced leaders, including direct interaction with the CEO. With a focus on innovation and proprietary technology, Dablam provides its team members with unique opportunities to contribute to impactful solutions in a rapidly evolving industry.

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Contact Details:

Dablam Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Senior AI & Data Engineer β€” Hybrid, Mentoring & Paid Leave

✨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 Dablam!

✨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 Senior AI & Data Engineer β€” Hybrid, Mentoring & Paid Leave at Dablam.

✨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 Dablam.

✨Apply Directly through Our Website

When you find a suitable opening like Senior AI & Data Engineer β€” Hybrid, Mentoring & Paid Leave at Dablam, 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 Senior AI & Data Engineer β€” Hybrid, Mentoring & Paid Leave

Analytics Engineering
Data Analysis
Clustering Techniques
Data Pipeline Development
Measurement Problem Solving
Communication Skills
Collaboration with Technical Teams

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 Dablam, 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 Dablam. 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 Dablam

✨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 Dablam!

✨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.