Data Scientist Computer Vision & Financial Intelligence
Erada
Posted 30+ days ago
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Nationality
Any Nationality
Gender
Not Mentioned
Vacancy
1 Vacancy
Job Description
Roles & Responsibilities
Key Responsibilities
- Computer Vision & OCR
- Financing & Risk Use Cases
- Model Development & Deployment
- Data Analysis & Feature Engineering
- Governance & Documentation
- Design and develop computer vision models for document analysis and image-based decisioning.
- Build and optimize OCR pipelines for:
- National IDs, contracts, application forms, and supporting documents.
- Low-quality, mobile-captured, real-world images.
- Implement image preprocessing and enhancement techniques to improve OCR and classification accuracy.
- Work on live / near-real-time image processing use cases when required.
- Apply data science techniques to financing-related problems such as:
- Customer onboarding and document verification.
- Fraud detection and anomaly identification.
- Creditworthiness and risk signal extraction.
- Translate business and regulatory requirements into measurable model outputs.
- Partner closely with risk, product, and engineering teams to ensure models are usable and explainable.
- Build, train, evaluate, and fine-tune ML models with a strong focus on accuracy, robustness, and bias control.
- Prepare models for production deployment, working closely with engineering teams.
- Monitor model performance post-deployment and iterate based on real-world data.
- Analyze structured and unstructured datasets (images, text, metadata).
- Engineer meaningful features from visual and non-visual data sources.
- Validate data quality and identify edge cases early.
- Ensure models align with regulatory, audit, and explainability requirements common in financial services.
- Clearly document methodologies, assumptions, limitations, and results.
- Communicate findings effectively to both technical and non-technical stakeholders.
Desired Candidate Profile
Required Qualifications
- 3+ years of hands-on experience as a Data Scientist or Applied ML Engineer.
- Strong practical experience in Computer Vision and OCR.
- Proven experience working with real-world image data (mobile photos, scanned documents, noisy inputs).
- Solid proficiency in Python and common data science libraries.
- Hands-on experience with PyTorch, TensorFlow, OpenCV, and OCR frameworks (e.g., Tesseract or similar).
- Strong understanding of machine learning fundamentals, model evaluation, and optimization.
- Experience deploying or supporting models in production environments.
- Familiarity with financial, lending, or risk-related data is highly preferred.
Nice to Have
- Experience with KYC, document verification, or identity-related systems.
- Exposure to fraud detection or credit risk models.
- Knowledge of model explainability techniques (SHAP, feature attribution, etc.).
- Experience working in regulated environments (FinTech, Banking, NBFI).
- Understanding of CI/CD or MLOps concepts.
Company Industry
- Banking
- Financial Services
- Broking
Department / Functional Area
- IT Software
Keywords
- Data Scientist Computer Vision & Financial Intelligence
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Erada
At Erada Finance, data and AI are core enablers of digital financing, customer onboarding, and risk decisioning.