Middle Data Scientist

FAVBET Tech develops software that is used by millions of players around the world for the international company FAVBET Entertainment.We develop innovations in the field of gambling and betting through a complex multi-component platform which is capable to withstand enormous loads and provide a unique experience for players.FAVBET Tech does not organize and conduct gambling on its platform. Its main focus is software development.

Main areas of work:

• Betting/Gambling Platform Software Development — software development that is easy to use and personalized for each customer.
• Highload Development — development of highly loaded services and systems.
• CRM System Development — development of a number of services to ensure a high level of customer service, effective engagement of new customers and retention of existing ones.
• Big Data — development of complex systems for processing and analysis of big data.
• Cloud Services — we use cloud technologies for scaling and business efficiency.

We are looking for a Middle Data Scientist to join our Data Science Team.

Responsibilities:

• Analyse big volumes of data to extract actionable insights.
• Build, validate, and deploy machine learning models.
• Design and conduct A/B tests to measure the impact of the new features.
• Collaborate with marketing and product teams to understand business needs and deliver data-driven solutions.
• Collaborate with engineering teams on data sources and feature processing.
• Present your results to business customers.

Required qualifications:

• Minimum 2 years of experience as a Data Scientist.
• Strong proficiency in SQL and Python, including commonly used machine learning libraries (e.g., scikit-learn, pandas, NumPy).
• Hands-on experience designing, running, and interpreting A/B tests.
• Familiarity with version control systems such as GitHub, GitLab, or Bitbucket.

Nice to have:

• Experience with cloud data services, preferably within the AWS ecosystem.
• Experience working with recommendation systems.
• Familiarity with Docker for containerization.
• Solid understanding of MLOps fundamentals.

We offer:

• 30 days off — we value rest and recreation.
• Medical insurance for employees and the possibility of training employees at the expense of the company and gym membership.
• Remote work or the opportunity — our own modern lofty office with spacious workplace, and brand-new work equipment (near Pochaina metro station).
• Flexible work schedule — we expect a full-time commitment but do not track your working hours.
• Flat hierarchy without micromanagement — our doors are open, and all teammates are approachable.