Lead Data Scientist
Lead Data Scientist
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Job Description
We are hiring on behalf of one of our clients a leading RegTech SaaS company that helps global enterprises in fintech banking and compliance sectors manage risk and regulatory requirements. The company leverages AI and data-driven insights to power its solutions and now seeks Lead Data Scientists to strengthen its product innovation and analytics capabilities.
Role Overview
As a Data Scientist you will play a critical role in designing developing and deploying machine learning and statistical models to solve complex business and compliance challenges. You will collaborate with engineering product and compliance experts to build scalable data-driven solutions that improve product accuracy efficiency and customer outcomes.
Key Responsibilities
- Collect clean and analyze large structured and unstructured datasets from multiple sources.
- Develop and implement machine learning models for fraud detection risk scoring identity verification and compliance monitoring.
- Conduct statistical analysis feature engineering and predictive modeling to extract insights and improve product performance.
- Collaborate with engineering teams to deploy models into production at scale.
- Partner with product teams to design experiments (A/B testing) and evaluate feature effectiveness.
- Research and implement state-of-the-art algorithms in AI/ML relevant to RegTech (e.g. anomaly detection NLP computer vision).
- Monitor evaluate and continuously improve models for performance fairness and compliance.
- Prepare clear documentation dashboards and reports to communicate findings to both technical and non-technical stakeholders.
Requirements
- Bachelors or Masters degree in Computer Science Data Science Statistics or a related field.
- 25 years of experience as a Data Scientist or ML Engineer (preferably in SaaS fintech or RegTech).
- Proficiency in Python R or Scala with strong knowledge of libraries such as scikit-learn TensorFlow PyTorch or similar.
- Strong understanding of statistics probability and machine learning techniques (classification clustering NLP anomaly detection).
- Experience working with SQL and NoSQL databases.
- Knowledge of big data tools (Spark Hadoop or similar) is a plus.
- Experience deploying ML models to production environments (AWS GCP or Azure).
- Strong analytical problem-solving and communication skills.
Preferred Skills
- Hands-on experience with computer vision techniques (e.g. object detection OCR facial recognition document image analysis).
- Expertise in deep learning frameworks (TensorFlow PyTorch Keras) applied to image-based models.
- Familiarity with image preprocessing techniques (augmentation noise reduction image normalization).
- Understanding of explainable AI in computer vision for compliance-driven use cases.
- Ability to translate complex image-based model outputs into product-ready solutions.
Employment Type
Full Time
