Job Description
Broad knowledge and experience in:
- Strong desire to grow career as Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets.
- Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques.
- Ability to apply latest mathematical and statistical techniques to analyze data and uncover patterns.
- Interested to build web application as part of job scope.
- Knowledge in Cloud based Analytics and Machine Learning Modeling
- Knowledge in building APIs for application integration.
- Knowledge in the areas: statistical modeling, feature extraction and analysis, feature engineering, supervised/unsupervised/semi-supervised learning.
- Data Analysis and Validation skills
- Strong software development skills.
Above average skills in:
- Programming Fluency in Python
- Knowledge in statistics, Machine learning and other advanced analytical methods
- Knowledge in javascript, AngularJS 2.0, Tableau will be added advantage.
- Knowledge in OOPS background is added advantage.
- Understanding of pySpark and/or libraries for distributed and parallel processing is added advantage.
- Knowledge in Tensorflow, and/or other statistical software including scripting capability for automating analyses
- Knowledge with time series data, images, semi-supervised learning, and data with frequently changing distributions is a plus
- Understanding of Manufacturing Execution Systems (MES) is a plus
Demonstrated ability to:
- Work in a dynamic, fast-paced, work environment
- Self-motivated with the ability to work under minimal direction
- To adapt to new technologies and learn quickly
- A passion for data and information with strong analytical, problem solving, and organizational skills
- Work in multi-functional groups, with diverse interests and requirements, to a common objective
- Communicate very well with distributed teams (written, verbal and presentation)