The Sports Betting Data Scientist performs standard & ad-hoc analyses and builds statistical & machine learning models to continuously monitor and optimize systems’ performance, support data-driven decision making and make actionable recommendations, aligned with Trading Team’s business needs.
Responsibilities
- Creates and maintains reports and dashboards that allow business stakeholders to continuously monitor performance in real time
- Recommends actions by analyzing, comparing and interpreting data and proposes changes to business owners
- Develops and maintains data preparation, quality, validation and aggregation, scalable and re-usable routines
- Develops and implements simulation tools that model the inter-relationship between different parameters and facilitate business decision making
- Identifies relevant tool optimization to achieve cost and quality efficiency
- Develops and implements predictive models to forecast the future estimated turnover and odds for the division’s offers in tournaments, events and markets
- Support building and maintaining the department’s data analysis and reporting infrastructure and platform, ensuring data integrity throughout
Qualifications
- A Bachelor’s Degree in Statistics, Applied Mathematics, Econometrics, Operational Research, Computer Engineering or related field with strong quantitative and/or programming focus. Also a Postgraduate Degree will be preferable
- 1-6 years of working or related research experience (evidenced by PhD and/or relevant publications, awards, or completed project credentials) with preferably at least 1 year in the sports betting industry
- Proven experience in Data modeling and Management, integration and manipulation of large disparate datasets (i.e. structured, semi-structured or unstructured)
- Proven experience in predictive modeling and optimization
- Strong skills in databases and statistical packages for data manipulation and development of predictive and prescriptive models (i.e. SAS, SPSS, SQL, or modern advanced analytics software such as R, Python)
- Experience in designing, building, testing and validating models using a large number of statistical and other quantitative techniques
- Advanced data visualization tools (Tableau, Spotfire, Qlikview, etc.) for integration between disparate data sources, design and implementation of KPIs and generation of automatic and scalable visualizations that facilitate extraction of business insights
- Familiarity with common SaaS tools and BI platforms (Salesforce.com, Mixpanel/Heap, Tableau/Looker, etc.) and ETL processes to support data integrations between those platforms
- Strong/excellent analytical and problem-solving skills
- Effective organizational and planning skills to deal with a variety of projects
- Very good interpersonal and communication skills (written and verbal) both in English and Greek languages
Benefits
The company offers excellent career opportunities and a competitive compensation package, based on the qualifications of the candidate.