Senior data scientist/machine learning engineer

About the Company: Our unique 4 G/5 G v RAN solution is designed to improve quality of experience, enhance spectral efficiency, provide flexibility to the operator in hardware selection, provide full network automation and significantly reduce Total Cost of Ownership (TCO). Our product is designed with leading edge hardware & software technologies. We have a team of passionate professionals who understand mobile network operator's requirements & vision. Our objective is to provide mobile network operators with the equipment required to deploy and expand their 4 G/5 G networks quickly and efficiently in the most feature rich and cost-effective way. Department Overview: Rakuten Symphony is at the forefront of revolutionizing the telecommunications industry, building and deploying cutting-edge Open RAN and cloud-native telecom software solutions globally. Our strategic vision is to enable a truly data-driven, intelligent network infrastructure. The AI/ML team within Rakuten Symphony plays a pivotal role in this transformation, leveraging advanced analytics and machine learning to optimize network performance, enhance operational efficiency, and develop innovative telecom services. Join Our Innovative Product Development Team We are seeking a highly skilled and experienced Senior Data Scientist / Machine Learning Engineer to join our dynamic and international AI/ML team. This is an end-to-end product-focused role within Rakuten Symphony, where you will be instrumental in designing, developing, and deploying AI/ML solutions specifically tailored for RAN (Radio Access Network) and broader telecom software product portfolios. Our team fosters a "missionary" culture, empowering team members to fully own their product responsibilities and develop hybrid skillsets. This means Data Scientists can expand their engineering and product expertise, while Machine Learning Engineers can engage in scientific research and gain product acumen. We value continuous learning, growth, and mutual respect among team members, operating with a flat organizational structure that minimizes hierarchy and fosters a collaborative environment. You will have the unique opportunity to work on solutions that directly impact the performance, reliability, and innovation of next-generation telecom networks, contributing to Rakuten Symphony's global leadership in the Open RAN space. Position: Senior Data Scientist / Machine Learning Engineer Why We Hire: We are expanding our AI/ML capabilities to accelerate the development and deployment of intelligent solutions across our RAN and telecom software product portfolio. We are looking for an experienced specialist who can leverage their deep expertise in data science and machine learning to address complex challenges in telecommunications, from network optimization and predictive maintenance to intelligent resource allocation and anomaly detection. This role is crucial for delivering cutting-edge AI/ML-driven features that provide a competitive advantage to our customers worldwide. Position Details: Join our dynamic, international, and agile AI/ML team to design, develop, and deploy advanced machine learning models and solutions that drive innovation within the RAN and telecom software domain. You will collaborate closely with cross-functional teams including RAN engineers, network architects, software developers, and product managers to deliver impactful AI/ML products. Our team focuses on critical areas within telecom and networking, including but not limited to: network performance optimization, predictive maintenance for network elements, intelligent resource management, anomaly detection, root cause analysis, security threat intelligence, and automation of network operations. You will be working with massive amounts of real-time and historical network data, leveraging state-of-the-art AI/ML techniques to extract actionable insights and build intelligent systems. Job Level: Senior (7+ years of experience) Objectives: Collaborate with RAN engineering, software development, and product teams to deeply understand business needs and identify opportunities for AI/ML application within the telecom domain. Research, design, and implement innovative statistical and machine learning models for complex telecom challenges, such as network optimization, fault prediction, and resource allocation. Clearly and effectively communicate complex technical findings, insights, and model performance to all stakeholders, including non-technical audiences. Enable smarter, more autonomous network operations and business processes by leveraging analytics and AI/ML to generate meaningful, actionable insights. Stay current with the latest advancements in AI/ML, particularly in the context of telecom and networking, to maintain cutting-edge expertise and drive continuous innovation. Responsibilities: Serve as a lead AI/ML strategist, identifying and integrating new datasets relevant to RAN and telecom operations that can be leveraged for AI/ML solutions. Work closely with engineering teams on the development of robust data pipelines and data products. Execute analytical experiments and build proof-of-concept models to solve challenging problems across various telecom domains. Identify relevant data sources and prepare large structured and unstructured datasets (e.g., call detail records, network performance counters, logs, alarm data) for AI/ML model training and validation. Devise and utilize advanced algorithms and models for large-scale telecom data analysis; perform rigorous data and error analysis to improve model accuracy and robustness; clean and validate data for uniformity and accuracy. Analyze network data for trends, patterns, and anomalies, interpreting data with clear objectives of improving network performance, reliability, and efficiency. Design, develop, and implement machine learning models into production environments, collaborating closely with product managers, software developers, and ML operations (MLOps) engineers to ensure seamless integration and deployment. Lead the entire ML lifecycle, from problem definition and data exploration to model development, testing, deployment, monitoring, and maintenance. Mandatory Qualifications: **Telecom & Networking Industry Knowledge and Experience** Minimum 7 years of professional experience as a Data Scientist or Machine Learning Engineer. Proven experience creating machine learning solutions specifically for the telecommunications and networking domains (e.g., RAN, Core Network, Transport Network). Broad knowledge and hands-on experience with a wide range of machine learning models and techniques. Deep expertise in areas such as time-series analysis, anomaly detection, predictive analytics, reinforcement learning, and optimization algorithms as applied to network data. Understanding of 4 G/5 G mobile network architectures, protocols (e.g., 3 GPP standards), and key performance indicators (KPIs) is highly preferred. Experience with network performance data, fault management systems, and operational support systems (OSS) is a significant plus. **Technical & Fundamental Skills** Master’s degree or higher in Data Science, Machine Learning, AI, Computer Science, Electrical Engineering, Telecommunications, Statistics, Physics, or related fields. (Ph D is a great plus). Proficiency in data preparation, feature engineering, and understanding of data quality challenges in large-scale, real-world datasets. Advanced experience in pattern recognition, predictive modeling, and statistical analysis. Expert-level proficiency in Python for data science and machine learning. Strong programming skills in C++ for performance-critical components or integration with existing telecom software stacks. Hands-on experience with major machine learning frameworks such as **Py Torch** and/or **Tensor Flow**. Experience with MLOps practices and tools for deploying, monitoring, and managing ML models in production environments (e.g., Docker, Kubernetes, Kubeflow, MLflow). Proficiency in SQL for data extraction and manipulation. Ability to write clean, maintainable, and well-documented code, adhering to software engineering best practices. Demonstrated ability to deliver ML models from research to successful production deployment. Experience with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services is a plus. **Fundamental Business Skills** Ability to work effectively in a dynamic, agile, product-oriented group managing multiple concurrent projects with tight deadlines. Strong problem-solving skills and a proactive approach to identifying and addressing complex technical challenges. Excellent communication skills, both written and verbal, with the ability to articulate complex technical concepts to diverse audiences. Strong collaboration skills, with the ability to work effectively in a cross-functional, international team environment. **Language** Fluent English communication skills (both written and spoken) are required as the team operates in English. Rakuten Shugi Principles Our worldwide practices describe specific behaviours that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success. Always improve, always advance. Only be satisfied with complete success - Kaizen. Be passionately professional. Take an uncompromising approach to your work and be determined to be the best. Hypothesize - Practice - Validate - Shikumika. Use the Rakuten Cycle to success in unknown territory. Maximize Customer Satisfaction. The greatest satisfaction for workers in a service industry is to see their customers smile. Speed Speed Speed Always be conscious of time. Take charge, set clear goals, and engage your team.