Ho Chi Minh
2017-09-18 -> 2017-09-19
- Solid understanding of statistical analysis, machine learning and data-modeling.
- Experience in predictive modeling and analysis.
- Practical experience with machine learning toolkits and frameworks
- At least 2-5 years of working experience using Java, Python, R in doing data engineering and data-modeling
- Possess at least a Degree or Diploma in computer science / IT related;
- Willingness to learn and able to pick up new technology or new concepts fast;
- Able to work independently as well as in collaborative mode with minimum supervision;
- Work productively even under pressure;
- Possess good work ethic, attitude with good follow-through;
- Excellent communication in written and spoken English.
- Knorex develops a cloud-based, highly scalable, all-in-one advertising and marketing platform called Knorex XPO™ (https://xpo.knorex.com/) where Advertisers, Agencies and Publishers can easily create, optimize & publish Dynamic Ads worldwide with speed and ease. As part of the platform offering, anyone can launch performance campaign and traffic their ads programmatically via automated buying through our in-house media planner, real-time bidder and optimizer. Owing to the large and real-time stream of data, we would have to devise efficient algorithms to tackle the challenges. We are seeking for a Data Scientist with the zest and passion to join us in developing the platform. You will be working with cross-disciplinary teams including Data Engineers, Performance Specialists and Software Engineers to build a highly intelligent and scalable system that can handle billions of requests per day, all delivered within milliseconds.
- In this role, you will be expected to possess solid experience in applying machine learning algorithms and statistical techniques to build highly accurate models. You need to acquire a deep technical understanding of the platform, and work with other team members to ensure the timely delivery of the planned tasks and critically assess and monitor the efficiency and/or effectiveness of the models.
- Key Responsibilities
- Develop clever algorithms and pragmatic solutions to our automation and optimization problems.
- Build high accuracy machine learning models that can learn and optimize performance from vast amount of data.
- Develop metrics to measure the outcome/impact of your introduced solutions.
- Work with other members to implement and integrate into our existing systems.
- Document and improve the solutions over time.
- Evaluate and identify new technologies for implementation.
- Communicate with our business and technical teams to understand the analytics requirements.
- Respond and follow up to incorporate feedback and draw new insights.
- Prioritize tasks to meet multiple deadlines.