At a Glance
- Tasks: Join a dynamic quant team to build and maintain data workflows for sports betting analysis.
- Company: BettingJobs, a growing player in the sports betting industry.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on problem-solving and continuous improvement.
- Why this job: Make an impact by ensuring high-quality data drives innovative modelling and research.
- Qualifications: Strong Python and SQL skills, with experience in data engineering and analysis.
The predicted salary is between 63000 - 77000 £ per year.
BettingJobs is seeking a Data Engineer to join a small but growing quant team in the sports betting industry. Working alongside the modelling team, you will be responsible for ensuring they have access to reliable, well-structured and high-quality data for research, modelling and analysis. From building robust Python-based workflows to investigating complex data issues and assessing new data sources, the Data Engineer will be responsible for extracting maximum value from the data.
Responsibilities:
- Work day-to-day with quant modellers to prepare, refine and maintain datasets used for research, modelling and analysis.
- Investigate data issues affecting modelling outputs, identifying root causes and working with relevant teams to resolve them.
- Build and maintain Python-based data workflows and pipelines for ingestion, transformation and validation of modelling data.
- Maintain and develop historical data assets, ensuring they remain accurate, accessible and fit for analytical use.
- Work with engineers to improve upstream and downstream data flows, ensuring critical data is captured and processed effectively.
- Ensure data quality and integrity through validation, reconciliation and targeted monitoring across key datasets.
- Expand visibility into data issues by improving checks, alerts and investigative workflows across critical pipelines.
- Define and improve data logic, transformations and assumptions, ensuring they are clearly documented and consistently applied.
- Support data migrations, backfills and structural improvements to improve the reliability of modelling datasets.
- Contribute to tooling and processes that make it easier to explore, prepare and troubleshoot data used by the quant team.
Requirements:
- Strong experience in a Quant Data Engineer, Research Data Engineer or similar role working with complex datasets.
- Understanding of the sports betting industry.
- Strong Python skills for data processing, investigation and workflow development.
- Excellent SQL skills and solid experience with relational databases, preferably PostgreSQL.
- Proven experience preparing, transforming and validating datasets for analytical, modelling or research use cases.
- Experience investigating data issues and tracing problems through pipelines, transformations and source systems.
- Experience building and maintaining data pipelines or processing workflows in production environments.
- Strong understanding of data quality, reconciliation and validation practices.
- Experience working with analytical data warehouse technologies such as ClickHouse, BigQuery, Snowflake or Redshift (beneficial).
- Experience with version control systems (preferably GitLab) and tools such as JIRA and Confluence.
- Comfortable working with messy, incomplete or evolving datasets and turning them into reliable assets.
- Experience working in Agile environments and collaborating with distributed teams.
- Excellent attention to detail, strong problem-solving ability and clear verbal and written communication skills.
Data Engineer - Quantitative Analysis in City of London employer: BettingJobs
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StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Quantitative Analysis in City of London
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We think you need these skills to ace Data Engineer - Quantitative Analysis in City of London
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 BettingJobs, 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 BettingJobs. 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 BettingJobs
✨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 BettingJobs!
✨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.
