Senior Data Scientist

Job Description

Join our Team About this opportunity: Ericsson Enterprise Wireless Solutions (BEWS) is responsible for driving Ericsson s Enterprise Networking and Security business. Our expanding product portfolio covers wide area networks, local area networks, and enterprise security. We are the #1 global market leader in Wireless-WAN enterprise connectivity and are rapidly growing in enterprise Private 5G networks and Secure Access Services Edge (SASE) solutions. What Will You Do: Define the Data sourcing strategy and works with partners to procure data. Supply to IP creation for Ericsson in AI/ML. Research studies and creative usage of new and/or existing data sources. Work with Data Architects to use existing data models and build new ones as needed. Work with new technologies and be the ambassador for them in MI Communities within Ericsson, nurturing the communities and mentoring junior data scientists. Engage with external ecosystem (academia, technology leaders, open source etc.) to develop the skills and technology portfolio for MI s needs Present and be prominent in MI related forums and conferences, e.g., publishing patents, presenting papers, organizing sessions etc. To be successful in the role you must have: Total 6 - 9 yrs of experience with proven skills of implementing a variety of Machine Learning techniques. Solid programming skills (R/Python) with proficiency in at least one. Proven track record of leading AI/ML projects end-to-end with complete ownership. Experience in Generative AI, conversation Assistant systems. Proven skills in building AI/ML based solutions using frameworks such as Python, R, H2O, Keras, TensorFlow, Spark ML etc. Experience in implementing new algorithms and methodologies from leading open source initiatives and research papers. Hands-on experience in designing and building AI models using Deep Neural Networks for applicable scenarios. Able to build and deploy AI models into production with focus on scaling, monitoring and performance. Sound knowledge of building explainable models (XAI) and prescriptive analytics.