Lead Machine Learning Engineer
3 days ago
Lead ML Engineer
This is a very inspiring role in Networks Digitization team where you will use your knowledge and/or experience in Data Science methodologies and apply them to develop analytics based solutions that produce telecom Networks and customer experience use cases as well as quantitative and qualitative business insights. You will work in a highly collaborative environment where you communicate and plan tasks and ideas.
Responsibilities and Duties:
- Responsible for developing scientific methods, processes, and systems to extract knowledge or insights to drive the future of applied analytics in Networks.
- Mine and analyze data from company databases to drive optimization and improvement of product development and business strategies.
- Assess the effectiveness of new data sources and data gathering techniques. Develop custom data models and algorithms to apply to data sets.
- Use predictive modeling to enhance Network experience customer experiences, revenue generation and other business outcomes.
- Must be able to communicate effectively and have detailed knowledge of data preparation and cleaning, algorithm selection & design, results analysis, industrialization.
- Work with stakeholders to understand business requirements and processes for projects so implementation can be done without delays.
- Work with partners as necessary to integrate systems and data quickly and effectively, regardless of technical challenges or business environments.
Qualifications and Skills:
- Solid understanding in Statistics, e.g., hypothesis formulation, hypothesis testing, descriptive analysis and data exploration.
- Good understanding in Machine Learning, e.g., linear/logistics regression discriminant analysis, bagging, random forest, Bayesian model, SVM, neural networks, etc.
- Strong programming skills in various languages (Python, Scala, R)
- Strong ambition to learn and implement current state of the art machine learning frameworks such as Scikit-Learn, TensorFlow, and Spark.
- Familiarity with Linux/OS X command line, version control software (git).
- Familiarity in programming or scripting to enable ETL development
- Familiarity with relational databases and SQL .
Academic Qualifications
Masters or equivalent advanced degree in Computer Science, Computer Engineering, Statistics, Mathematics or related technical discipline.
Experience LevelSenior Level-
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