Big Data Algorithm Engineer, DD&T, Chengdu

• Collect and analyze large datasets from diverse sources to drive key business insights.
• Develop machine learning models, including supervised and unsupervised learning techniques, to predict and optimize business outcomes.
• Implement and optimize deep learning architectures and algorithms such as neural networks and reinforcement learning.
• Construct data architectures, models, and protocols to identify trends and insights.
• Create visualizations and dashboards to present data insights to stakeholders clearly and effectively.
• Work collaboratively with cross-functional teams to integrate machine learning insights into business strategies.
• Manage projects independently and provide guidance to junior professionals.
• Stay updated with the latest trends and advancements in machine learning and data science, applying them as needed.

• Solid educational background in mathematics, computer science, statistics, economics, or related fields.

• Proven 3+ years of experience as a Data Scientist or in similar role
• Proficient in programming languages such as Python and R, with a strong emphasis on machine learning libraries (e.g., scikit-learn, TensorFlow, Keras, PyTorch).
• Strong understanding of machine learning algorithms, including regression, classification, clustering, and dimensionality reduction techniques.
• Experience with deep learning frameworks and building complex neural network models.
• Expertise in natural language processing (NLP) techniques and applications.
• Proficiency in data visualization tools like Tableau or Power BI, and ability to communicate findings effectively.
• Strong data manipulation and database management skills, including SQL.
• Analytical thinking and problem-solving skills with the ability to develop innovative solutions.
• Strong business acumen and ability to translate machine learning insights into actionable business strategies.
• Excellent communication and interpersonal skills for effective collaboration with stakeholders.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud for deploying machine learning models is a plus.
• Knowledge of AutoML platforms and emerging technologies like generative AI.
• Proficiency in English (both spoken and written)

Takeda