What you will be doing…
This role will be responsible for analyzing large, complex datasets and identifying meaningful patterns that lead to actionable recommendations. This role will be performing thorough testing and validation of models, and supporting various aspects of the business with data analytics.
- Responsible for the design, development, testing, deployment, maintenance, and improvement of machine learning system software.
- Leverages big data tools and programming frameworks to ensure that the raw data gathered from data pipelines are redefined as data science models that are ready to scale as needed.
- Asserts that production ML tasks are working properly and ensures that data science code is maintainable and scalable in terms of actual execution and scheduling, ensuring that data science code is maintainable and scalable.
- Uses experience, expertise and skills to make recommendations and solve problems that are more difficult and infrequent.
- Develop and deploy knowledge-based structures to be used by various teams, systems, and tools.
- Develop tools and processes to maintain, monitor, and enhance existing knowledge-based structures, ensuring their ongoing performance.
- Identify and implement various sources of data from across the company to further improve knowledge-based structures.
- Utilize feedback from users and reports to identify gaps and resolve issues.
- Work with clients to gather requirements and recommend possible solutions to business initiatives.
What we are looking for…
You'll need to have:
- Bachelor’s degree or four or more years of work experience.
- Four or more years of relevant machine learning experience.
- Experience in Machine learning algorithms including: forecasting, clustering, classification, reinforcement learning, deep learning etc.
- Experience in Spark and/or Python.
- Strong experience in Big Data Analysis.
- Experience with Generative AI and GPU solution optimization.
- Good mobile telecommunications industry knowledge, including experience with handset manufacturers, network equipment vendors, and/or chipset vendors.
- Ability to do statistical modeling, build predictive models and leverage machine learning algorithms, build efficient ML pipeline.
Even better if you have one or more of the following:
- Strong communication skills to collaborate with cross-functional teams and explain technical concepts.
- Strong analytical capabilities, creativity and critical thinking.
- Excellent problem-solving skills and ability to debug complex issues across the entire stack.