Data Scientist for Sports Betting Analytics

hace 2 semanas


Barcelona, Barcelona, España buscojobs España A tiempo completo

Estimate Salary: $120,000 - $180,000 per year

About the Company

Workfully is a decentralized hiring and upskilling marketplace. The company's vision is to give everyone an opportunity to build a better world.

About the Role

This position involves leveraging statistical analysis, machine learning techniques, and predictive modeling to extract insights from large datasets and improve the accuracy of betting odds and outcomes.

Key Responsibilities
  1. Analyze large datasets to identify trends, patterns, and correlations related to sports events, betting markets, and customer behavior.
  2. Develop predictive models and algorithms to forecast sports outcomes, optimize betting odds, and inform trading strategies.
  3. Collaborate with cross-functional teams to integrate predictive models into our platform and products.
  4. Conduct exploratory data analysis to uncover actionable insights and opportunities for optimization across various aspects of the sports betting ecosystem.
  5. Design and implement experiments to test hypotheses and evaluate the performance of predictive models, iterating based on results and feedback.
  6. Stay abreast of advancements in data science, machine learning, and sports analytics research, incorporating new methodologies and techniques into our analytics toolkit.
  7. Communicate findings and recommendations to stakeholders clearly and concisely, both verbally and through data visualization techniques.
Requirements
  1. Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. An advanced degree or relevant certification is a plus.
  2. Proven experience as a Data Scientist or similar role, with a strong portfolio showcasing your work.
  3. Proficiency in programming languages such as Python, with experience in data analysis libraries like Pandas, NumPy, and SciPy.
  4. Experience with database technologies including MongoDB and SQL, with the ability to write complex queries and perform data manipulation and analysis.
  5. Strong understanding of statistical analysis, machine learning, and data mining techniques, with hands-on experience applying these methods to solve real-world problems.
  6. Knowledge of data visualization tools like Matplotlib, Seaborn, or Tableau, with the ability to communicate complex insights effectively.
  7. Experience working with large datasets and distributed computing frameworks like Apache Spark or Hadoop is a plus.
  8. Strong problem-solving skills and analytical thinking, with the ability to interpret data, identify trends, and draw actionable insights.
  9. Effective communication and collaboration skills, with the ability to work cross-functionally with stakeholders to understand business requirements and deliver solutions.
  10. Passion for continuous learning and self-improvement, with a curiosity to explore new tools, technologies, and methodologies in the field of data science.

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