Senior Data Scientist

ZingBrain AI; Poland; On-site; PLN 254,993 - 339,991; Full time

Benefits offered by this job

Medical compensation

Paid sick leaves

Compensation for sports activities

Well-being webinars and workshops

Language learning bonus €150 per month

80% paid professional employee training

Job summary

ZingBrain AI in Poland is looking for a Senior Data Scientist to develop ML-driven features for casino games and maintain recommendation systems. The ideal candidate will have over 5 years of experience, a degree in a quantitative field, and proficiency in Python and SQL. Responsibilities include collaborating with cross-functional teams, analyzing datasets, and deploying ML models to production. The position offers remote work flexibility and various wellness and development benefits.

Qualifications

• 5+ years of experience in data science.
• Strong engineering skills to design and maintain scalable ML solutions.
• Ability to structure and solve loosely defined problems.

Responsibilities

• Collaborate with cross-functional teams on project success.
• Analyze large datasets to inform product decisions.
• Propose and evaluate machine learning approaches.

Skills

Proficiency in Python

Proficiency in SQL

Data manipulation tools (Pandas, Polars)

Knowledge of Docker

Knowledge of Kubernetes

Supervised ML techniques (XGBoost, LightGBM)

Statistical methods (A/B testing)

Education

Degree in a quantitative field (Mathematics, Statistics, Computer Science)

Tools

Airflow

Valkey/Redis

FastAPI

Job description

About Us

We're an international product company in the gambling sector. ZingBrain AI personalizes casino content in real time using advanced machine learning, helping operators boost player engagement, retention, and ultimately revenue. Our mission is to empower gambling businesses worldwide by streamlining their operations and elevating the player experience with groundbreaking features.

WHO WE'RE LOOKING FOR

At Zingbrain, we build real‑time personalization systems for iGaming platforms. Our models operate in production, influencing what each user sees — from game recommendations to sportsbook event suggestions — based on live behavioral, transactional, and contextual data.

We’re looking for a Senior Data Scientist to join our team and help us in the following areas:

• Develop ML-driven features for casino games using supervised learning (regression, ranking, classification)
• Maintain and enhance the existing recommendation systems in production, including:
  • Model enhancement using gradient boosting methods
  • Data cleaning and preprocessing
  • Pre- and post-processing workflows
  • Optimization of training and inference pipelines
  • Integration of ML models into Airflow pipelines in a multi‑tenant environment
  • Adapt and configure the solution for different clients (tenants)

This is a hands‑on role involving modeling, experimentation, and close collaboration with engineering and product teams in a high‑load, real‑time environment.

AS A PART OF OUR TEAM YOU WILL

• Collaborate with cross‑functional teams of data scientists, engineers, product owners, designers, and researchers to ensure project success
• Analyze large datasets to extract actionable insights that inform product decisions
• Propose, implement, and evaluate machine learning approaches to solve business problems, working closely with Product Owner(s)
• Maintain and adopt the current recommendation solution in a multi‑tenant environment
• Influence product strategy through research and experimentation that deepens understanding of how product features, platforms, and promotions affect user behavior

What We Expect

Experience and education

• 5+ years of experience in data science
• A degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science)

Core skills

• Proficiency in Python, SQL, and data manipulation tools (Pandas, Polars)
• Strong engineering skills to design, build, and maintain scalable ML solutions, including implementing observability across pipelines through metrics, logging, and alerting.
• Knowledge of Docker, Kubernetes.
• Ability to structure and solve loosely defined problems, delivering actionable insights for product development; strong analytical mindset with both numerical and business understanding
• Hands‑on experience with supervised ML techniques (regression and ranking using XGBoost, LightGBM, CatBoost, or neural networks), including feature engineering, model evaluation (AUC, NDCG, MSE, uplift metrics), and personalization or recommendation systems
• Proven experience deploying ML models to production for near real‑time or batch processing
• Solid knowledge of statistical methods (A/B testing, significance testing, etc.)

Nice to have

• Production experience with large-scale recommendation systems
• Production experience with Airflow, Valkey/Redis, FastAPI
• Familiarity with contextual bandits or reinforcement learning for online optimization is a plus
• Familiarity with AutoML is a plus

Our Benefits

Wellness program

• Medical compensation
• Paid sick leaves
• Compensation for sports activities
• Well‑being webinars and workshops

Work & Life Balance

• Wellness Day: 4th Friday off monthly
• Remote work
• 21 working days of vacation
• 5 personal days per year

Professional Development

• English speaking club
• Language learning bonus €150 per month
• 80% paid professional employee training
• Provided tech equipment

Extra Advantages

• €150 for the arrangement of the workplace
• Bonuses for significant events and additional personal days if necessary
• Offline and online company parties and team buildings