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Quantitative Analytics Professional
2 weeks ago
The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from complex data sets to ask the right questions and find the right answers.
Responsibilities- Raw Data Analysis: Assess quality, cleanse, and structure for downstream processing
- Prediction Algorithm Design: Create accurate, scalable, and efficient prediction models
- Collaboration with Engineering Teams: Transition analytical prototypes into production systems
- Actionable Insights Generation: Drive business improvements and decision-making
- Dashboard Development: Maintain dashboards and reports for stakeholders
- Education: Bachelor's or Master's degree in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
- Professional Experience: 3–5 years of professional experience in quantitative analytics, data modeling, or applied machine learning
- Technical Skills: Strong understanding of predictive modeling, machine learning, clustering, classification techniques, and algorithms; Proficiency in programming languages such as Python, R, SQL
- Big Data Experience: Hands-on experience with big data frameworks and cloud environments (e.g., Hadoop, Spark, GCP, AWS, or Azure)
- Data Visualization Tools: Familiarity with data visualization tools (Tableau, Power BI, or equivalent)
- Problem-Solving Mindset: Strong problem-solving mindset and ability to communicate complex concepts to non-technical stakeholders