Senior AI/ML Solutions Engineer

Responsibilities & Deliverables

• Design, develop, and deploy scalable machine learning models to solve complex business problems in the financial services domain.

• Collaborate with data scientists, data engineers, and business stakeholders to understand requirements and translate them into technical solutions.

• Build and maintain ML pipelines for data preprocessing, model training, evaluation, and deployment using MLOps best practices.

• Conduct exploratory data analysis and feature engineering to improve model performance and interpretability.

• Monitor model performance in production and implement retraining strategies to ensure accuracy and relevance over time.

• Contribute to the development of AI-driven products and services, including fraud detection, credit scoring, customer segmentation, and predictive analytics.

• Ensure compliance with data privacy, security, and regulatory standards (e.g., GDPR, Fair Lending).

• Document model development processes, assumptions, and performance metrics for transparency and audit readiness.

• Stay current with advancements in AI/ML technologies and recommend innovative solutions to enhance business capabilities.

Required Skills & Experience

• 3 + years of experience in machine learning, data science, or AI engineering .

• 5+ years experience supporting global data governance and data management initiatives, preferably in the banking , fintech or other highly regulated industries.

• Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch , or XGBoost .

• Strong understanding of supervised and unsupervised learning, model evaluation techniques, and statistical analysis.

• Experience with cloud platforms (e.g., Azure ML, AWS SageMaker, or GCP AI Platform) and containerization tools (e.g., Docker, Kubernetes).

• Familiarity with MLOps tools and practices for versioning, CI/CD, and model monitoring.

• Experience working with large-scale datasets and distributed data processing frameworks (e.g., Spark, Databricks).

• Knowledge of financial services use cases and key performance indicators (e.g., risk modeling, transaction classification, customer behavior analytics).

• Excellent problem-solving and communication skills, with the ability to explain complex models to non-technical stakeholders.

Qualifications

• Bachelor s or Master s degree in Computer Science , Data Science, Statistics, or a related field; PhD is a plus.

• Strong understanding of data governance principles, metadata management, data quality, and data management frameworks.

• Proven ability to support strategic implementation, manage change, and deliver results under tight deadlines.

• Excellent interpersonal skills with a demonstrated ability to collaborate effectively with cross-functional stakeholders, including product, legal, privacy, risk, and security teams.

• Exceptional written and verbal communication skills in English.

• Professional certifications in data governance (e.g., CDMP, ADGP, IGP) are advantageous .