招聘&找人AI产品数据工程师

Position Overview
We are seeking a talented and experienced Data Scientist to join our team and lead the development of AI models for a variety of predictive and classification applications. The ideal candidate will have a strong background in statistical modeling, machine learning, and data analysis. You will be responsible for building robust models to solve complex problems across multiple domains, including but not limited to credit risk, fraud detection, customer segmentation, and demand forecasting.
Key Responsibilities
• Model Development: Design, develop, and implement predictive and classification models for various applications, including but not limited to credit risk, fraud detection, customer segmentation, and demand forecasting.
• Data Collection and Preparation: Aggregate, clean, and preprocess data from multiple sources, ensuring high data quality and integrity.
• Feature Engineering: Develop and transform features from raw data, including normalization, scaling, ratio calculations, log transformations, binning, and handling outliers.
• Algorithm Selection: Evaluate and select appropriate machine learning algorithms (e.g., logistic regression, decision trees, random forests, gradient boosting machines, neural networks) based on the problem context and data characteristics.
• Model Training and Evaluation: Train models using cross-validation and other techniques, and evaluate model performance using metrics such as ROC-AUC, accuracy, precision, recall, and F1 score.
• Data Balancing: Implement techniques to address class imbalances, such as oversampling, undersampling, and synthetic data generation.
• Model Interpretation and Documentation: Ensure models are interpretable and document the modeling process, including assumptions, methodologies, and results.
• Collaboration: Work closely with stakeholders across different departments to integrate models into business processes and systems.
• Continuous Improvement: Stay updated with the latest advancements in machine learning and AI, and continuously improve models based on new data and feedback.
Qualifications
• Education: Master’s or Ph.D. degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
• Experience: 3+ years of experience in data science, with a focus on predictive modeling and classification.
• Technical Skills:
• Proficiency in programming languages such as Python or R.
• Strong knowledge of machine learning frameworks and libraries (e.g., scikit-learn, XGBoost, TensorFlow, Keras).
• Experience with data preprocessing, feature engineering, and handling large datasets.
• Familiarity with database systems and SQL.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Analytical Skills: Strong problem-solving skills and the ability to analyze complex data sets.
• Communication Skills: Excellent written and verbal communication skills, with the ability to present complex technical information to non-technical stakeholders.
• Teamwork: Ability to work collaboratively in a team environment and manage multiple projects simultaneously.
Preferred Qualifications
• Experience with credit risk modeling, fraud detection, customer segmentation, or demand forecasting.
• Knowledge of regulatory requirements and compliance in relevant domains.
• Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure).
• Experience with big data technologies (e.g., Hadoop, Spark).