Deskripsi Pekerjaan
Capgemini is a global leader in consulting, technology services, and digital transformation. We are currently seeking a talented AI Data Scientist to join our dynamic team in Kuala Lumpur. In this role, you will leverage advanced analytics, machine learning, and AI techniques to drive innovation and deliver measurable business value for our clients across diverse industries.
You will work closely with cross‑functional teams to design, develop, and deploy scalable AI solutions that turn complex data into actionable insights. This is an exciting opportunity to shape the future of AI‑powered transformations, contribute to cutting‑edge projects, and accelerate your career in a fast‑paced, collaborative environment.
At Capgemini, we believe in continuous learning and development. As part of our team, you will have access to world‑class training, mentorship programs, and a global network of experts, enabling you to stay ahead of emerging technologies and trends.
Tanggung Jawab
- Design, build, and deploy machine learning models and AI algorithms to solve business challenges.
- Collaborate with data engineers and domain experts to ensure data quality, integrity, and accessibility.
- Translate analytical findings into clear, actionable recommendations for stakeholders.
- Lead end‑to‑end data science projects from problem definition to model deployment and monitoring.
- Continuously research and evaluate new AI technologies, frameworks, and best practices.
- Mentor junior data scientists and promote a culture of data‑driven decision making.
- Document methodologies, code, and results to ensure reproducibility and knowledge sharing.
Kualifikasi
- Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
- Proven experience in developing and deploying machine learning models in production environments.
- Proficiency in programming languages such as Python, R, or Scala.
- Strong expertise in deep learning frameworks (e.g., TensorFlow, PyTorch) and cloud platforms (AWS, Azure, GCP).
- Solid understanding of data engineering concepts and experience with big data technologies (Spark, Hadoop).
- Excellent communication skills with the ability to present complex results to non‑technical audiences.
- Experience with MLOps, model monitoring, and CI/CD pipelines for AI solutions is highly desirable.
- Relevant certifications (e.g., Google Professional Data Engineer, Microsoft Certified: Azure AI Engineer) are a plus.