Remote Senior Product Data Analyst β€” AI, Experiments & Impact

Remote Senior Product Data Analyst β€” AI, Experiments & Impact

Full-Time 60000 - 80000 Β£ / year (est.) Working from home possible
Kraken

At a Glance

  • Tasks: Lead a data team and build scalable data infrastructure for impactful insights.
  • Company: Join Kraken, a leading fintech company with a focus on innovation.
  • Benefits: Remote work, competitive salary, and opportunities for professional growth.
  • Other info: Work in a dynamic environment with a collaborative culture.
  • Why this job: Shape the future of fintech with your data expertise and drive real business impact.
  • Qualifications: 10+ years in data analytics, strong skills in SQL and Python.

The predicted salary is between 60000 - 80000 Β£ per year.

Kraken is seeking a Senior Data Analyst, Product to take ownership of the product domain end-to-end. The role involves leading a collaborative data team, building scalable data infrastructure, and influencing business decisions through data-driven insights.

With a requirement of 10+ years in data analytics, proven experience in fintech, and deep knowledge in SQL and Python, the ideal candidate will shape technical direction and drive impactful data strategies. This position is remote, open to applicants in the UK.

Remote Senior Product Data Analyst β€” AI, Experiments & Impact employer: Kraken

At Kraken, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. As a remote employer based in the UK, we offer flexible working arrangements, competitive benefits, and ample opportunities for professional growth in the fast-paced fintech sector. Join us to be part of a forward-thinking team where your insights will directly influence impactful business decisions.

Kraken

Contact Details:

Kraken Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Remote Senior Product Data Analyst β€” AI, Experiments & Impact

✨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 Kraken!

✨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 Remote Senior Product Data Analyst β€” AI, Experiments & Impact at Kraken.

✨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 Kraken.

✨Apply Directly through Our Website

When you find a suitable opening like Remote Senior Product Data Analyst β€” AI, Experiments & Impact at Kraken, 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 Remote Senior Product Data Analyst β€” AI, Experiments & Impact

Data Analytics
SQL
Python
Data Infrastructure Development
Collaboration
Business Decision Influence
Data-Driven Insights

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 Kraken, 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 Kraken. 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 Kraken

✨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 Kraken!

✨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.