Key Responsibilities
**
- Design, develop, and deploy machine learning models for diverse use cases, including RegTech applications, predictive analytics, natural language processing, and computer vision.
- Experiment with cutting-edge algorithms and frameworks to drive innovation and solve challenging problems.
- Optimize models for scalability, performance, and real-time deployment.
- Build and manage end-to-end ML pipelines, encompassing data collection, preprocessing, model training, deployment, and monitoring.
- Implement MLOps best practices, including CI/CD pipelines, model versioning, and production monitoring.
- Lead a high-performing ML team, define team goals, and foster a culture of collaboration and innovation.
- Take proactive ownership of projects, identify opportunities for value creation, and explore innovative ML approaches tailored to regulatory technology challenges.
- Partner with cross-functional teams to align ML projects with business and compliance goals.
- Conduct research to advance the application of ML in RegTech and other key domains.
- Document models, pipelines, and processes to ensure clarity, reproducibility, and knowledge sharing.
**Challenges We Are Tackling:**
- Identity Fraud Detection
- Intelligent Document Processing
- Motor Insurance & Finance
- Contract Lifecycle Management
- User Knowledge Graph
**Key Qualifications:**
**Education and Experience:**
- Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, or a related field (PhD preferred).
- 4+ years of experience in ML/AI, with a strong track record of successful model deployments.
- Preferred experience in RegTech/Fintech or an interest in applying ML in Fintech solutions.
**Technical Skills:**
- Expertise in ML frameworks and tools.
- Strong understanding of MLOps platforms and cloud infrastructure.
- Proficiency in Python, and experience with big data tools.
- Familiarity with regulatory and compliance systems is a plus.
- Working with unstructured document information is nice to have.
**Soft Skills:**
- Innovation-driven mindset with a passion for tackling complex challenges.
- Strong leadership, mentoring, and team-building skills.
- Excellent problem-solving abilities and an ability to take initiative.
- Exceptional communication skills for both technical and non-technical stakeholders. As a Machine Learning (ML) Lead in this role, you will have the exciting opportunity to spearhead ML initiatives, drive innovation, and foster a culture of mentorship and collaboration. You will be responsible for developing and deploying machine learning models for diverse use cases, including RegTech applications, predictive analytics, natural language processing, and computer vision. Your role will also involve building and managing end-to-end ML pipelines, leading a high-performing ML team, and taking proactive ownership of projects to deliver impactful ML-driven solutions.
**
Key Responsibilities
**
- Design, develop, and deploy machine learning models for diverse use cases, including RegTech applications, predictive analytics, natural language processing, and computer vision.
- Experiment with cutting-edge algorithms and frameworks to drive innovation and solve challenging problems.
- Optimize models for scalability, performance, and real-time deployment.
- Build and manage end-to-end ML pipelines, encompassing data collection, preprocessing, model training, deployment, and monitoring.
- Implement MLOps best practices, including CI/CD pipelines, model versioning, and production monitoring.
- Lead a high-performing ML team, define team goals, and foster a culture of collaboration and innovation.
- Take proactive ownership of projects, identify opportunities for value creation, and explore innovative ML approaches tailored to regulatory technology challenges.
- Partner with cross-functional teams to align ML projects with business and compliance goals.
- Conduct research to advance the application of ML in RegTech and other key domains.
- Document models, pipelines, and processes to ensure clarity, reproducibility, and knowledge sharing.
**Challenges We Are Tackling:**
- Identity Fraud Detection
- Intelligent Document Processing
- Motor Insurance & Finance
- Contract Lifecycle Management
- User Knowledge Graph
**Key Qualifications:**
**Education and Experience:**
- Bachelors or Masters degree in Computer Sci
