Data Scientist
- PhD in Computer Science, Computer Engineering, Statistics, Math or Analytics.
- Understanding of Multivariate statistics – regression, principal components analysis and clustering
- Understanding of Big Data technologies including Hadoop, MapReduce, Hive, Pig, Cassandra and Machine Learning R, Python, PHP, Ruby, Matlab, JAVA, C++, SQl, SAS, SPSS.
- Develop and plan required analytic projects in response to business needs.
- In conjunction with data owners and department managers, contribute to the development of data models and protocols for mining production databases.
- Manage and/or provide guidance to junior members of the team.
- Functional Experience envelopes the key areas such as Applied AI in Data Analytics, Machine Learning.
- Analytic Problem-Solving: Approaching high-level challenges with a clear eye on what is important; employing the right approach/methods to make the maximum use of time and human resources.
- Effective Communication: Detailing your techniques and discoveries to technical and non-technical audiences in a language they can understand.
- Intellectual Curiosity: Exploring new territories and finding creative and unusual ways to solve problems.
- Industry Knowledge: Understanding the way Telecom functions and how data are collected, analysed and utilized.
- Evaluate the models that are running in the POC’s .
- Collaborate and work closely with cross functional teams to identify gaps and structure problems.
- Create Meaningful presentations and analyses that will give out focused insights.
- Propose technical solutions for the Use cases : Output – Mathematical Models, System Accuracy and flow diagram of the machine learning process.
- Evaluate the data in the system to come with probable problem statements and convert them in to use-cases.