Senior Data Scientist
March 20
Description
• Sitting at the intersection of business and engineering • Improve decision-making capabilities and connect people to relevant experiences • Contribute to full project life-cycle from ideation to production • Form a tight-knit group focused on upskilling and fostering a culture of excellence • Highly visible role with potential to define scope and strategy • Define Fever's data culture • Solid understanding of math, statistics, and Machine Learning fundamentals • Master common data and ML tools • Ability to turn ideas into reality and work effectively with cross-functional teams • Scientific mindset, problem-first attitude, and self-critical approach • Entrepreneurial spirit, thrive in a fast-paced environment • Comfortable with software engineering best practices • Excellent communication skills and proficient in business English
Requirements
• Solid math, statistics, and Machine Learning fundamentals (MSc or PhD level) • Ability to understand algorithm theory, make informed modeling choices, and evaluate proposal performance • Ability to build quick prototypes and robust analysis pipelines • Ability to translate complex problems into mathematical formulations and construct solid baselines • Comfortable with introducing complexity when needed • Strong entrepreneurial spirit, take ownership of work, communicate effectively, take risks, and leave things better • Comfortable with writing robust, reproducible, and maintainable code • Excellent proficiency in business English • Plus: Expertise in technical areas such as Bayesian modeling, causal inference, real-world recommendation systems • Relevant work experience in marketing or
Benefits
• Fully integrated into the team and meet key partners on the engineering and business sides • Navigate data assets • Familiarize with Fever’s tech stack and frameworks • Attend Fever Original’s experiences like Candlelight • Understand the full business context and identify key challenges • Contribute significantly to advance a challenging Data Science project • Participate in hackdays or hackathons with other teams • Establish yourself as a sought-after collaborator • Mentor new joiners and contribute to the data science and analytics community • Have input in planning the Data Science org and influence partners' roadmaps
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