Machine Learning Engineer

We are seeking a motivated and inquisitive individual who is passionate about tackling intricate lending challenges through novel approaches. This person should possess the ability to leverage their expertise to conduct thorough data analysis, transforming complex information into user-friendly formats that can be easily understood by various business units and stakeholders. The ideal candidate should be comfortable working collaboratively in a team environment and possess excellent communication and presentation skills. As a Data Scientist, this role will report directly to the team lead in machine learning.

Responsibilities:

•  Design end-to-end machine learning (ML) production systems, including project scoping, data requirements, modeling strategies, and deployment considerations.
• Establish a baseline model, address concept drift, and prototype the development, deployment, and continuous improvement of ML applications in a production environment.
• Build robust data pipelines by collecting, cleaning, and validating datasets. Implement data lineage and provenance metadata tools to manage the data lifecycle effectively.
• Apply best practices and progressive delivery techniques to ensure the smooth operation and ongoing monitoring of production systems.

Requirements:

• Master’s Degree in Computer Science, Operations Research, Engineering, or a related quantitative discipline.
• 2-5 years of experience in programming languages such as Python, SQL, or Scala.
• Strong understanding of quantitative analysis methods as applied to financial institutions.
• Ability to effectively communicate modeling results to diverse audiences.
• 5+ years of hands-on experience in building and implementing AI/ML solutions, suitable for a senior role.
• Proficiency in Python libraries such as Numpy, scikit-learn, OpenCV, Tensorflow, Pytorch, Flask, and Django.
• Experience with source version control systems like Git and Bitbucket.
• Proven knowledge of Rest API, Docker, Google Big Query, and VScode.
• Strong analytical skills and a data-driven mindset.

It is advantageous if you have:

• Prior experience in image processing or natural language processing.
• Solid understanding of customer analytics.
• Familiarity with MLOps methodologies.