
Unlock Data Potential
1 day ago
The ideal candidate excels in extracting valuable insights from complex data sets to drive business growth.
Responsibilities:
- Analyze raw data: assess quality, cleanse, and structure for downstream processing
- Design accurate, scalable, and efficient prediction algorithms
- Collaborate with engineering teams to transition analytical prototypes into production systems
- Generate actionable insights to inform strategic decision-making
- Develop and maintain dashboards and reports for stakeholders
Qualifications:
- Bachelor's or Master's degree in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
- 3–5 years of professional experience in quantitative analytics, data modeling, or applied machine learning
- Strong understanding of predictive modeling, machine learning, clustering, classification techniques, and algorithms
- Proficiency in programming languages such as Python, R, SQL (knowledge of C/C++/Java is a plus)
- Hands-on experience with big data frameworks and cloud environments (e.g., Hadoop, Spark, GCP, AWS, or Azure)
- Familiarity with data visualization tools (Tableau, Power BI, or equivalent)
- Strong problem-solving mindset and ability to communicate complex concepts to non-technical stakeholders
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