工作内容:

About the Role

We are seeking a Data Mining Engineer to join our AI & Analytics team.

You will be responsible for transforming large-scale IoT and sensor data into actionable insights and predictive models.

Your work will directly support industrial applications such as anomaly detection, predictive maintenance, and operational optimization across various domains.

Responsibilities

Design and implement data cleaning and preprocessing pipelines for large-scale IoT and industrial sensor data.

Conduct exploratory data analysis (EDA) to uncover patterns, correlations, and anomalies.

Perform feature engineering and statistical modeling to extract valuable information from high-frequency and time-series data.

Develop and deploy machine learning and statistical models for anomaly detection, forecasting, and predictive maintenance.

Build and maintain data visualization dashboards and analytical reports to communicate findings effectively to business and technical stakeholders.

Collaborate closely with data engineers, domain experts, and software developers to ensure end-to-end model integration and deployment.

Continuously evaluate model performance and improve algorithms for robustness, scalability, and accuracy.

Contribute to technical documentation, presentations, and data-driven reports for internal and external stakeholders.

职位要求:

Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, Statistics, Electrical Engineering, or a related field.

Strong Python programming skills, with experience in scientific and data analysis libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, TensorFlow, statsmodels).

Solid understanding of time-series analysis, signal processing, and statistical modeling techniques.

Experience with data cleaning, missing data handling, and outlier detection in noisy IoT environments.

Familiarity with machine learning algorithms (e.g. clustering, regression, anomaly detection, forecasting models).

Experience in working with industrial, manufacturing, or IoT datasets is a strong plus.

Proficiency in SQL and experience with databases or data warehouses (e.g. PostgreSQL, InfluxDB, TimescaleDB).

Good command of English communication skills — able to document technical work and present findings clearly.

Strong analytical mindset and ability to derive insights from complex datasets.

Preferred Qualifications

Experience with streaming or real-time data pipelines (e.g. Kafka, Flink, or Spark Streaming).

Familiarity with cloud platforms such as AWS, Azure, or GCP for data storage and model deployment.

Hands-on experience with Docker / Kubernetes for model serving and deployment.

Knowledge of edge AI or on-device model optimization for IoT applications.