Senior Data Scientist

Why should you choose us

Rakuten Symphony is reimagining telecom, changing supply chain norms and disrupting outmoded thinking that threatens the industry's pursuit of rapid innovation and growth. Based on proven modern infrastructure practices, its open interface platforms make it possible to launch and operate advanced mobile services in a fraction of the time and cost of conventional approaches, with no compromise to network quality or security. Rakuten Symphony has operations in Japan, the United States, Singapore, India, South Korea, Europe, and the Middle East Africa region. For more information, visit: https://symphony.rakuten.com

Building on the technology Rakuten used to launch Japan's newest mobile network, we are taking our mobile offering global.

To support our ambitions to provide an innovative cloud-native telco platform for our customers, Rakuten Symphony is looking to recruit and develop top talent from around the globe. We are looking for individuals to join our team across all functional areas of our business – from sales to engineering, support functions to product development.

Let's build the future of mobile telecommunications together!

About Rakuten Group, Inc. (TSE: 4755) is a global leader in internet services that empower individuals, communities, businesses and society. Founded in Tokyo in 1997 as an online marketplace, Rakuten has expanded to offer services in e-commerce, fintech, digital content and communications to approximately 2 billion members around the world. The Rakuten Group has over 30,000 employees, and operations in 30 countries and regions. For more information visit https://global.rakuten.com/corp/.

Job Summary:

We are looking for an experienced and highly motivated Senior Data Scientist with 5–10 years of industry experience to drive advanced analytics, machine learning, and AI initiatives. The ideal candidate should possess strong expertise in statistical modeling, predictive analytics, data engineering concepts, and large-scale data processing. This role involves working closely with cross-functional teams to solve complex business problems and build scalable data-driven solutions.

Key Responsibilities:

• Design, develop, and deploy machine learning and AI models for real-world business problems.
• Perform exploratory data analysis (EDA), feature engineering, and model optimization.
• Build predictive, classification, recommendation, anomaly detection, and forecasting models.
• Work with large-scale structured and unstructured datasets using distributed computing frameworks.
• Collaborate with product, engineering, business, and analytics teams to define data-driven strategies.
• Develop scalable data pipelines and ensure data quality and governance standards.
• Interpret model outputs and present insights to technical and non-technical stakeholders.
• Monitor model performance in production and implement continuous improvement mechanisms.
• Stay updated with latest advancements in AI/ML, Generative AI, LLMs, and MLOps practices.
• Mentor and guide best practices across the team.

Required Skills:

Technical Skills

• Strong programming skills in Python and/or R.
• Expertise in machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
• Hands-on experience with statistical modeling and data analysis techniques.
• Strong SQL knowledge and experience with large-scale databases.
• Experience with big data technologies such as Spark, Hadoop, Hive, or Trino.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of MLOps tools and model deployment pipelines.
• Experience with APIs, microservices, and container technologies like Docker/Kubernetes is a plus.
• Exposure to Generative AI, LLMs, vector databases, and RAG frameworks is preferred.

Analytical & Business Skills

• Strong problem-solving and analytical thinking.
• Ability to translate business problems into data science solutions.
• Excellent communication and stakeholder management skills.
• Experience working in Agile environments.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field.

Preferred Experience

• 5-10 years of hands-on experience in Data Science, Machine Learning, or AI.
• Experience working in telecom, cloud, networking, fintech, e-commerce, or enterprise platforms is an advantage.
• Prior experience handling production-grade ML systems at scale is highly preferred.

Nice to Have

• Experience in Graph Analytics, Network Analytics, or Telecom KPI analysis.
• Knowledge of anomaly detection systems and observability platforms.
• Familiarity with OpenTelemetry, Kubernetes ecosystem, or distributed systems analytics.

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.