Bridge the gap between data science and data engineering to design and implement high-impact analytical solutions.
Responsibilities
- Design and build data processing pipelines, data models, and engineering workflows to drive information visualization.
- Develop predictive analytics and modeling methods, including simulations, using deep learning architectures.
- De-mystify AI and client models to ensure transparency and explainability for stakeholders.
- Execute model governance and manage model risk in alignment with MDLC requirements.
- Collaborate with subject matter experts across the organization to provide technical direction and data strategy.
Required Skills
- 5+ years of experience in data science, data mining, or data engineering.
- Degree in mathematics, statistics, computer science, or a related technical field.
- Hands-on experience with Python, PySpark, and PyTorch.
- Proficiency with deep learning toolkits including TensorFlow and Keras.
- Experience with the Hadoop platform, including Spark and Kafka.
- Strong background in hypothesis testing, regression analysis, and probability.
- Fluency in SQL with relational databases such as MySQL or Oracle.
- Knowledge of R or SAS.
- Experience with model governance and model risk management.
Preferred Skills
- Advanced degree in Engineering, Mathematics, Statistics, or Computer Science.
- Background in text analytics, news aggregation, and natural language processing.
- Six Sigma Black Belt or Master Black Belt certification.