DATA SCIENTIST

Accountabilities • Develop, implement, and productionize machine learning models that improve personalization, search ranking, and recommendation systems. • Design and build data-driven algorithms that enhance user experience and drive measurable improvements in engagement and conversion rates. • Apply advanced statistical methods and data mining techniques to extract insights from large-scale datasets. • Collaborate with engineering and product teams to integrate ML models into production systems and ensure scalability and reliability. • Continuously monitor model performance and iterate based on real-world data and business feedback. • Translate business problems into analytical and machine learning solutions with clear impact on key performance indicators. • Work with cloud infrastructure and data pipelines to support scalable ML workflows. • Contribute to experimentation and A/B testing frameworks to validate model effectiveness. Requirements • Minimum of 2 years of experience as a Data Scientist, Quantitative Analyst, Quantitative Researcher, or similar analytical role. • Strong proficiency in Python and its data science ecosystem (e.g., pandas, NumPy, scikit-learn or similar tools). • Solid foundation in probability, statistics, machine learning, and linear algebra. • Proven experience applying ML models to real-world business problems with measurable impact on revenue or key metrics. • Good knowledge of SQL and experience working with relational databases. • Experience working with cloud platforms such as AWS, GCP, or Microsoft Azure is highly desirable. • Familiarity with productionizing ML models and working in end-to-end data science pipelines. • Comfortable working in a fast-paced, product-oriented environment with cross-functional stakeholders. • Strong communication skills and ability to explain technical concepts to non-technical audiences. • Bachelor’s or Master’s degree in Applied Mathematics, Computer Science, Engineering, Financial Engineering, or a related quantitative field. • Experience using AI tools or agents as part of the development workflow is considered an advantage. • Knowledge of Apache Spark and/or experience in the gaming industry is a plus. Benefits • Fully remote-first organization with flexible working arrangements. • Competitive salary with quarterly performance-based bonuses. • 28 days of paid annual leave. • Flexible working hours with core availability between 10am and 3pm local time. • Provision of high-end equipment to support your work. • Annual company retreats for collaboration and team networking. • Referral and performance-based bonus programs. • Opportunity to work on large-scale machine learning systems with direct business impact. • Strong emphasis on professional growth and exposure to modern ML and cloud technologies. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1