Description

Join our dynamic team and dive into a universe of professional opportunities! You'll develop and support large-scale projects across PC, console, and mobile platforms, creating innovative products across diverse genres, from casual to shooters.

Your Mission

• Automate Marketing Analytics: Develop and implement automated marketing analytics solutions using proprietary models.
• Hypothesis Testing & Investigation: Design and conduct rigorous testing and investigation of hypotheses to drive data-driven insights.
• Predictive Algorithm Development: Design and develop simple yet effective predictive algorithms to forecast trends and optimize strategies.
• Procurement Collaboration & Analysis: Collaborate with the procurement team to formulate key metrics and analyze procurement effectiveness.
• Data Visualization & Reporting: Create and visualize dashboards to present research results and insights to stakeholders.

What You Bring

• Proven Experience: 5+ years of experience as an Analyst and Developer, with 2+ years specifically in an Analyst/ML Engineer role.
• Python Proficiency: Strong Python skills, capable of working with large codebases.
• Predictive Modeling Expertise: Experience in developing and implementing predictive models.
• Data Visualization Skills: Experience creating and visualizing dashboards (using any BI stack) or presenting research results clearly.
• SQL Expertise: Proficiency in SQL (any database).
• Applied Mathematics Knowledge: Strong understanding of applied math areas, including time series analysis, advanced A/B testing, and classical ML algorithms.
• Customer Interaction: Ability to work effectively with customers.
• Cross-Functional Collaboration: Ability to collaborate seamlessly with ETL engineers and other analysts.

Bonus Points

• Advanced Education: Higher education in mathematics or a related technical field.
• Marketing Metrics Knowledge: Solid understanding of basic online marketing metrics.
• Spark Experience: Experience with Spark (or a strong willingness to learn).
• Continuous Learning: A commitment to continuous self-learning through articles, courses, and open-source contributions.