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.

Education

Any Graduate