Description

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.

Key Skills

Education

Any Graduate