WHY WE NEED YOU:
Are you experienced with building statistical and machine learning models, understanding deep mathematical and statistical concepts underneath, and being technically skilled to implement and maintain those models and end-to-end solutions, by following CI/CD standards? Detecting opportunities and applying your expertise to real-life business problems by collaborating with other roles, and seeing how your solutions impact millions of our players, while in the process helping with growing more junior data scientists?
If so, then you are in the right place!
WHAT YOU’LL DO:
- Perform A/B tests and causal inference analyzes in pvp games, while exploring research and development phases, as well as testing cutting-edge methodologies in the domain of causal inference, such as: Econometrics, Bayesian AB testing, DoubleML, Structural Causal Modeling, etc. (~30%)
- Utilize ML by building new or changing existing productional ML models and pipelines in order to provide a personalized experience to our users, make end-to-end DS solutions, and support decision-making. (~30%)
- Build elegant and scalable game systems, based on behavioural mathematics, game theory, and simulations, such as MatchMaking algorithms in PvP gaming environment (~15%)
- Be involved in defining telemetry tracking and designing DB schemas, working on ETL, performing ad hoc analyses and making reports, monitoring the performance of the game/features, and answering ad hoc data requests. (~15%)
- Work on arbitrary business problems, that can be solved by utilizing the DS toolbox including: forecasting KPIs and behaviours, developing data science standalone tools, performing Clustering, using Association rules, etc. (~10%)
WHAT WE’RE LOOKING FOR:
- 3+ years of experience in Data Science or related field
- Bachelor's degree in Computer Science, or other quantitative fields
- Experience with any OOP, as well as Python, Julia or R, and SQL.
- Strong knowledge of Statistics and Machine Learning concepts
- Excellent verbal and written skills in English
- Playing games, or following the Gaming industry
BONUS:
- Any experience with cloud computing (such as GCP, AWS, Azure, …) for ML and data infrastructure, big data tools (such as Databricks, Snowflake, Spark, Hadoop, …), or proficiency in MLOps (model deployment, versioning, CI/CD)
WHY YOU’LL LOVE WORKING HERE:
- The competitive compensation package, perks and benefits: unlimited vacation days, flexible working hours, hybrid ways of working, premium private medical insurance for you and your family (additional coverage for your parents is available with a participation fee), offsites for the whole company, fully-paid maternity leave, employee stock purchase plan, access to L&D platforms and opportunities, fitness reimbursement and many more.
- State-of-the-art workspace: Nordeus provided breakfast, lunch, snacks, and beverages, a 24/7 available fully-equipped gym, organised sports activities (yoga, Brazilian jiu-jitsu, basketball, football), an ergonomic workstation, top-notch tech equipment (including laptop, mobile phone and bill coverage, and other tech), a kids’ playroom, a music corner, golf simulator, board and video games + latest consoles. We make sure your life at Nordeus is hassle-free.
- High level of creative freedom: trust, respect, and teamwork are the essence of who we are. We inspire and support each other to bring the joy of winning to the lives of millions.
- Playing your part in the future of our games: with over 300M registered users, Top Eleven is the world’s most successful football management game. Golf Rival, with more than 60M registered users, is the #2 mobile golf game aiming to claim the top spot. With one more game in the works, we are continuing our efforts to create powerful gaming experiences built to last.
- Working with experienced game makers: you will be a part of a multicultural team of over 280 employees from different countries.
- Making an impact: we are putting Serbia on the global gaming map and working closely with the local community to develop the gaming ecosystem.