Senior Data Scientist (OCR)

We are looking for a self-motivated, naturally curious person interested in solving complex lending issues in new and innovative ways. This individual must utilize expertise to query, design and translate complex data analysis into simple, user-friendly mediums that are easily digestible by business units and stakeholders. Candidates must be comfortable working on a team and have strong communication and presentation skills.

Job responsibilities :

• Apply best practices and progressive delivery techniques to maintain and monitor a continuously operating production system.
• Build data pipelines by gathering, cleaning, and validating datasets. Establish data lifecycle by using data lineage and provenance metadata tools.
• Maintain and optimize a mission-critical production environment driven by complex business logic and ML; responsible for full-stack system diagnostics, deep-dive root cause analysis, and ensuring robust deployment standards.
• Establish a strategy or model baseline, address concept drift, and prototype how to develop, deploy, and continuously improve a productionized ML application.
• Collaborate with product managers, engineers, and business stakeholders to shape AI/ML strategy, prioritize initiatives, and align data science outcomes with business objectives.

Requirement skills :

• Bachelor’s or Master’s Degree in Computer Science, Engineering, or related quantitative discipline.
• 1-3 years of experience in programming languages such as Python and SQL.
• 1+ years of hands-on experience in building & implementing AI/ML solutions.
• Experience with python libraries - Numpy, scikit-learn, Pandas, OpenCV, Tensorflow,

PyTorch.

• Experience with source version control (Git, Bitbucket), Docker, Google Big Query.
• Exceptional analytical and strategic thinking skills; able to translate ambiguous business problems into well-defined data science solutions

It is great if you have

• Experience in image processing, OCR (Optical Character Recognition), and document understanding at scale.
• Experience with MLOps platforms (Vertex AI) and cloud-based infrastructure (GCP, AWS, or Azure).
• Experience with Large Language Models (LLMs), Generative AI, or NLP.