The ideal candidate will:
- Work with clients, managers and technical staff to understand business needs and develop technical plans to deliver results.
- Develop, deploy, and implement predictive models and protocols for mining production data sources.
- Appropriately deliver existing analytic methods and tools; applying theory to practice.
- Learn new analytic methods and tools as needed.
- Create analytic models and test hypotheses collaboratively in a rapid-paced work environment to meet client needs.
- Be accountable for data science solution delivery and code quality check including providing detailed and constructive design and code reviews.
- Help establish standards in machine learning and statistical analysis to ensure consistency in quality across projects and teams.
- Lead data science consulting engagements on the ground.
Requirements
- Have a strong foundation in statistics and data analytics with expertise in survey research and statistical modeling.
- Be able to create structure out of semi-structured and unstructured data using one or more data science toolkits such as Python, Machine learning and Natural language processing.
- Familiar with applied statistics such as probability distributions, measures of dispersion and central tendency, hypothesis testing and statistical inference.
- Have a keen understanding of the business value perspective on predictive analytics; Have experience deploying and monitoring predictive models.
- Possess excellent oral, written communication, presentation, and analytical skills.
Comments
Post a Comment
Leave your comment here...