What are the responsibilities and job description for the Data Scientist position at Macpower Digital Assets Edge Private Limited?
Job Description
Job Description
Job Summary : This position is with a Data Science consulting firm specialized in providing analytic solutions to clients in Commercial and Government industries. Providing analytic solutions to hundreds of companies across numerous industries, our team enjoys a great variety in the type of work they do and exposure to a wide range of techniques and tools. To fill this role, you must have Active TS / SCI security clearance with the full scope Polygraph that is required.
Position Responsibilities : A data scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.
Required Degree and Experience : Bachelor's degree in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science) 7 years of experience, Master's Degree 5 years of experience, or PhD 2 years of experience
Required Skills :
- Programming experience with data analysis software such as R, Python, SAS, or MATLAB.
- Develop experiments to collect data or models to simulate data when required data are unavailable.
- Develop feature vectors for input into machine learning algorithms.
- Identify the most appropriate algorithm for a given dataset and tune input and model parameters.
- Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices).
- Oversee the development of individual analytic efforts and guide team in analytic development process.
- Guide analytic development toward solutions that can scale to large datasets.
- Partner with software engineers and cloud developers to develop production analytics.
- Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation.
