ML Data Scientist End-to-End Models for Betting (Hybrid)

ML Data Scientist End-to-End Models for Betting (Hybrid)

Full-Time 50000 - 70000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and deploy data science solutions that drive business impact in the betting industry.
  • Company: Kwiff Ltd., a forward-thinking company in the betting tech space.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and continuous improvement.
  • Why this job: Join a dynamic team and make a real impact with cutting-edge data science techniques.
  • Qualifications: Experience in data science, machine learning, and strong analytical skills.

The predicted salary is between 50000 - 70000 £ per year.

Kwiff Ltd. is seeking a Data Scientist to design and deploy data science solutions that drive business impact.

You will work within the Data team on advanced analytics, ML, and data engineering, collaborating with commercial stakeholders to translate challenges into scalable solutions.

You’ll build models, design data workflows, and continuously improve data science practices while staying current with industry advances in data science and betting tech.

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ML Data Scientist End-to-End Models for Betting (Hybrid) employer: Kwiff Ltd

At kwiff, we pride ourselves on being an innovative employer that champions a player-first approach to sports betting. Our dynamic work culture fosters growth and learning, offering comprehensive benefits such as private healthcare, performance bonuses, and a hybrid working model that allows for flexibility. Join us in our Chiswick office, where you'll not only gain invaluable experience in the iGaming industry but also enjoy regular team socials and a supportive environment that values diversity and inclusion.

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Contact Details:

Kwiff Ltd Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land ML Data Scientist End-to-End Models for Betting (Hybrid)

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 Kwiff Ltd!

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 ML Data Scientist End-to-End Models for Betting (Hybrid) at Kwiff Ltd.

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 Kwiff Ltd.

Apply Directly through Our Website

When you find a suitable opening like ML Data Scientist End-to-End Models for Betting (Hybrid) at Kwiff Ltd, 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 ML Data Scientist End-to-End Models for Betting (Hybrid)

Data Science
Machine Learning (ML)
Data Engineering
Advanced Analytics
Model Building
Data Workflow Design
Collaboration with Stakeholders

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 Kwiff Ltd, 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 Kwiff Ltd. 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 Kwiff Ltd

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 Kwiff Ltd!

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.