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- Tasks: Lead data modeling and analysis for sports forecasting products.
- Company: Join an innovative betting company in the heart of London.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and collaboration.
- Why this job: Be at the forefront of sports analytics and make impactful contributions to exciting projects.
- Qualifications: 5 years in sports betting analytics, advanced statistical modeling skills, and Python expertise required.
- Other info: Collaborate with a passionate team and leverage cutting-edge technology.
The predicted salary is between 43200 - 72000 £ per year.
BettingJobs are currently recruiting for a Senior NBA Data Scientist based in London for an innovative betting company.
Responsibilities:
- Lead the development of models and supervise ad hoc analysis using a variety of data sources to solve tasks relevant to the business (e.g. supporting development of existing and/or new sports forecasting products).
- Extract meaningful insight from sports data using sound Mathematical/Statistical principles.
- Collaborate with and lead other members of the Data Science team to propose ideas and solve modelling problems relating to new/existing products.
- Follow typical development processes in terms of code management and structure.
- Liaise with various teams around the business (including Model Engineering and Data Collection teams where appropriate) to assist with tasks relevant to the modelling team.
Requirements:
- 5 years’ experience in sports betting/analytics industry in a quantitative or data science role.
- Possesses significant experience and a passion for statistical modelling of MLB or NBA.
- Advanced knowledge of statistical modelling and machine learning, with relevant experience in the use of relevant Python libraries e.g. scikit-learn, xgboost, tensorflow, pymc3, statsmodels (and R equivalents).
- Experience generating reports, dashboards and data visualisations to explain the results and behaviour of models.
- Experience with concurrent development source control (GIT).
- Familiarity with SQL and experience working with relational databases.
- Excellent presentation, documentation, time management, communication skills with the ability to work collaboratively and autonomously.
- Strong problem-solving skills with a pragmatic and analytical outlook.
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Senior NBA Data Scientist employer: SitePoint Pty.
Contact Detail:
SitePoint Pty. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior NBA Data Scientist
✨Tip Number 1
Make sure to showcase your experience in sports betting and analytics during networking events or meetups. Engaging with professionals in the industry can help you learn about unadvertised opportunities and gain insights into what companies like us are looking for.
✨Tip Number 2
Familiarize yourself with the latest trends in statistical modeling and machine learning, especially as they relate to NBA data. Being able to discuss recent advancements or case studies in your interviews will demonstrate your passion and expertise in the field.
✨Tip Number 3
Consider contributing to open-source projects or creating your own projects that utilize Python libraries relevant to data science. This not only enhances your skills but also provides tangible examples of your work that you can discuss during interviews.
✨Tip Number 4
Prepare to discuss your problem-solving approach in detail. We value candidates who can articulate their thought process and methodologies when tackling complex modeling challenges, so be ready to share specific examples from your past experiences.
We think you need these skills to ace Senior NBA Data Scientist
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Senior NBA Data Scientist position. Understand the key responsibilities and requirements, especially the emphasis on statistical modeling and experience in the sports betting industry.
Highlight Relevant Experience: In your CV and cover letter, emphasize your 5 years of experience in the sports betting or analytics industry. Provide specific examples of projects where you used statistical modeling and machine learning techniques relevant to NBA or MLB.
Showcase Technical Skills: Clearly list your technical skills, particularly your proficiency with Python libraries like scikit-learn, xgboost, and tensorflow. Mention any experience with SQL and GIT, as these are crucial for the role.
Prepare a Strong Cover Letter: Craft a compelling cover letter that not only outlines your qualifications but also demonstrates your passion for sports data science. Discuss how you can contribute to the development of new sports forecasting products and your approach to problem-solving.
How to prepare for a job interview at SitePoint Pty.
✨Showcase Your Statistical Modelling Skills
Be prepared to discuss your experience with statistical modelling, especially in the context of NBA or MLB. Highlight specific projects where you applied advanced techniques and the impact they had on the outcomes.
✨Demonstrate Your Technical Proficiency
Familiarize yourself with the Python libraries mentioned in the job description, such as scikit-learn and xgboost. Be ready to explain how you've used these tools in past projects, and consider bringing examples of your work.
✨Prepare for Collaborative Scenarios
Since collaboration is key in this role, think of examples where you've successfully worked with cross-functional teams. Be ready to discuss how you communicated complex data insights to non-technical stakeholders.
✨Discuss Your Problem-Solving Approach
Prepare to talk about specific challenges you've faced in your previous roles and how you approached solving them. Emphasize your analytical mindset and any innovative solutions you implemented.
