Data Scientist

2 weeks ago


Chennai Tamil Nadu, India Ford Motor Company Full time

Have a proven track record in the areas of Analytics and BI Implementation.
- Have a good amount of experience in business analysis, customer front-ending, eliciting requirements and problem solving.
- Have hands-on experience delivering Predictive models and analytics architecture.
- Have a good knowledge on more complex algorithms like Support Vectors, Artificial Neural Networks and Gradient Boosting.
- Have shown flexibility in taking up functional roles across different technologies.
- Have a proven track record in leading, motivating and liaising with teams, being a very strong team player.
- Have hands-on expertise in various Analytics/BI Tools like R, SPSS, MicroStrategy, Power BI, OBIA, Cognos, SAP BI, SSIS, Teradata, SQL Server. Have a conceptual exposure to Big Data with hands-on over Apache Spark with R.
- Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
- MS/ Phd in computer science or relevant experience
- 5 years of experience in analytical space.
- Strong in any python, java script, Java & C++
- Experience in Sklearn, Tensor flow or Pytorch
- Experience with machine or deep learning methods.
- Experience in operating linux based system
- Experience in SQL, Big data processing and Hadoop
- Experience in engineering SaaS based software development
- Experience in designing distributed system.
- Develop machine learning models and implement ML feature delivery as managed services or on device model.
- Collaborate with data engineers to develop data and model pipelines
- Write production-level code and bring code to production
- Engage in code reviews
- Design and evaluate approaches for handling large volume of real data streams.
- Improve existing machine learning models
- Develop prototype for future exploration.
- Be in charge of the entire lifecycle (research, design, experimentation, development. deployment, monitoring, and maintenance)
- Produce project outcomes and isolate issues
- Implement machine learning algorithms and libraries
- Communicate complex processes to business leaders
- Analyze large and complex data sets to derive valuable insights
- Research and implement best practices to enhance existing machine learning infrastructure


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