Data Scientist
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The Data Scientist will be responsible for designing and implementing processes and layouts for complex, large-scale data sets used for modelling, data mining, and research purposes.
This individual is also responsible for business case development, planning, coordination/collaboration with various internal and vendor teams, project managing the lifecycle of an analysis project,
and interface with business sponsors to provide periodic updates. The role will require working on multiple projects simultaneously.
Skill requirement :
- 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.
Role :
- 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.
Scope to be delivered :
- 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.
Bring Other industry Models and see the applicability In telecom services domain
