About Betfair Romania Development:
Betfair Romania Development is the largest technology hub of Flutter Entertainment, with over 2,000 people powering the world’s leading sports betting and iGaming brands. Exciting, immersive and safe experiences are delivered to over 18 million customers worldwide, from our office in Cluj-Napoca. Driven by relentless innovation and commitment to excellence, we operate our own unbeatable portfolio of diverse proprietary brands such as FanDuel, PokerStars, SportsBet, Betfair, Paddy Power, or Sky Betting & Gaming.
Our Values:
The values we share at Betfair Romania Development define what makes us unique as a team. They empower us by giving meaning to our contributions, and they ensure that we consistently strive for excellence in everything we do. We are looking for passionate individuals who align with our values and are committed to making a difference.
Win together | Raise the bar | Got your back | Own it | Positive impact
About Betnacional:
Founded in 2021, Betnacional was among the first betting platforms to secure a definitive operating license in Brazil. Known for its speed, innovation, and strong connection with Brazilian players, Betnacional combines cutting-edge technology with a deep understanding of the national market. In 2025, Betnacional together with Betfair Brazil have established Flutter International’s fifth region: Flutter Brazil.
Role Overview:
As a Data Scientist, your mission is to transform complex data into actionable insights that support strategic decisions and power data products across the organization. You’ll work on the full lifecycle of data science solutions—from exploratory analysis and feature engineering to predictive modeling and deployment—bringing measurable value to business, product, and customer outcomes.
You’ll be part of a cross-functional, innovation-driven data team, collaborating with engineers, analysts, product managers, and business stakeholders. With access to a modern data platform and a rich ecosystem of structured and unstructured data, you’ll help unlock insights using statistical modeling, machine learning, and experimentation frameworks.
Key Accountabilities & Responsibilities:
Deliver Data Science Projects: Work with your team to execute end-to-end data science projects, including data collection, preprocessing, feature engineering, model development, validation, and deployment.
Statistical Analysis: Apply advanced statistical techniques to analyze large datasets and uncover patterns, trends, and correlations that provide valuable insights to support business objectives.
Machine Learning and Modelling: Develop and implement predictive and prescriptive models using machine learning algorithms and techniques, such as regression, classification, clustering, time series analysis, natural language processing, and deep learning.
Data Visualization: Create clear and compelling visualizations to effectively communicate complex analytical findings.
Cross-Functional Collaboration: Collaborate with different teams, including product and engineering.
Performance Optimization: Continuously improve the accuracy, efficiency, and scalability of existing models and algorithms, and identify areas for optimization and innovation.
Collaboration: Work closely with other data scientists and contribute to building a strong data science team.
Stay Updated: Keep abreast of the latest advancements in data science, machine learning, and related fields, and proactively identify opportunities to leverage emerging technologies and techniques.
Use computers or computer systems (including hardware and software) to program, write programs, set up functions, enter data, or process information.
What You’ll Learn and Be Exposed To:
Real-world applications of ML in areas like personalization, customer behavior, fraud detection, LTV prediction, and sports analytics.
Working with a modern data stack (Databricks, Redshift, Athena, Airflow, dbt, Unity Catalog).
Best practices in deploying, monitoring, and maintaining machine learning pipelines.
Exposure to domain experts from betting, gaming, customer success, and marketing.
Compliance-aware modeling practices aligned with privacy and regulatory frameworks (LGPD/GDPR).
Continuous learning culture with access to mentorship, tech talks, and research exploration.
Skills, Capabilities & Experience Required:
Education: Bachelor’s, Master’s, or Ph.D. in a quantitative field such as Data Science, Computer Science, Statistics, Engineering, or equivalent practical experience.
Experience: At least 2 years in data science or applied ML roles, ideally with hands-on delivery of projects from ideation to production.
Programming: Proficiency in Python for data analysis, modeling, and automation.
Machine Learning: Solid understanding of algorithms (regression, classification, clustering, NLP, etc.), plus experience with libraries such as Scikit-learn, LightGBM, XGBoost, TensorFlow, or PyTorch.
Statistics: Deep knowledge of hypothesis testing, A/B testing, time series, and probabilistic modeling.
Data Skills: Strong skills in SQL, data wrangling, and feature engineering. Experience with Spark or distributed computing is a plus.
Visualization: Ability to communicate findings with tools like matplotlib, seaborn, Power BI, or Tableau.
Cloud & Environments: Familiarity with ML services on Databricks, AWS, GCP, or Azure; use of Docker, virtual environments (Anaconda), and CI/CD pipelines.
Analytical Skills: Strong problem-solving ability, critical thinking, and capacity to interpret complex data.
Communication: Strong verbal and written communication skills in English.
Adaptability: Ability to work in a fast-paced, dynamic environment and adapt to changing priorities.
Continuous Learning: A passion for learning and staying up-to-date with the latest trends and advancements in data science, machine learning, and related fields.
Differentials:
Experience in experimentation design (e.g., AB/n tests, uplift modeling).
Working knowledge of Databricks and MLflow for scalable model training and tracking.
Familiarity with MLOps practices and automated model monitoring.
Experience building data products in cross-functional teams, especially within digital or gaming platforms.
Contributions to open-source or internal knowledge-sharing initiatives.
Understanding of data privacy and ethical AI principles.
Benefits:
Hybrid & remote working options
€1,000 per year for self-development
Company share scheme
25 days of annual leave per year
20 days per year to work abroad
5 personal days/year
Flexible benefits: travel, sports, hobbies
Extended health, dental and travel insurances
Customized well-being programmes
Career growth sessions
Thousands of online courses through Udemy
A variety of engaging office events
Disclaimer:
We are an inclusive employer. By embracing diverse experiences and perspectives, we create a lasting, positive impact for our employees, customers, and the communities we’re part of. You don't have to meet all the requirements listed to apply for this role. If you need any adjustments to make this role work for you, let us know, and we’ll see how we can accommodate them.
We thank all applicants for their interest; however, only the candidates who best meet the job requirements will be contacted for an interview.
By submitting your application online, you agree that your details will be used to progress your application for employment. If your application is successful, your details will be used to administer your personnel record. If your application is unsuccessful, we will retain your details for a period no longer than three years, to consider you for prospective roles within the company.