Data Scientist Lead - Vice President

Join a team building secure, scalable, and reliable machine learning solutions that support critical business outcomes.

You will work across the full lifecycle-from exploratory analysis and model development to deployment, monitoring, and continuous improvement.

This role blends hands-on applied machine learning with strong engineering practices to deliver production-grade AI systems.

As a Data Scientist Lead - Vice President in the Chief Technology Office, you deliver end-to-end AI and machine learning solutions that are secure, stable, and scalable.

You conduct applied research, build and improve models, and design production-grade workflows for deployment and monitoring.

You collaborate closely with engineers and stakeholders to define integration patterns, testing strategies, and reliability standards.

You support delivery in regulated environments through strong documentation and operational readiness practices.

Job Responsibilities


* Perform data exploration and analysis to assess distributions, data quality issues, leakage risks, missingness, bias, and anomalies, and define data readiness criteria.


* Conduct applied research to evaluate modeling approaches (classical machine learning, deep learning, and generative AI where relevant), and document findings, trade-offs, and recommendations.


* Build baseline models and iteratively improve performance through feature engineering, error analysis, and interpretability techniques.


* Design and deploy generative AI applications, including fine-tuning, Retrieval-Augmented Generation systems, and agentic AI frameworks.


* Build and maintain automated machine learning workflows for training, evaluation, packaging, deployment, and monitoring with a focus on reliability and reproducibility.


* Apply infrastructure-as-code practices to provision and manage AWS resources for AI and machine learning workloads.


* Collaborate with engineers to define deployment and integration patterns (batch, real-time, event-driven) and testing strategies.


* Design and implement testing strategies (unit, component, integration, end-to-end, performance, and champion/challenger where appropriate).


* Mentor team members on coding practices, AI and machine learning best practices, and maintainable implementation patterns.


* Contribute to design reviews, operational readiness reviews, and documentation to raise overall engineering quality.


* Support delivery in regulated environments by participating in documentation, reviews, and audit readiness activities.

Required Qualifications, Capabilities, and Skills


* Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field with 7+ years of relevant experience.


* Hands-on experience with data exploration and data validation (leakage, bias, missingness, outliers, and data quality) using frameworks such as PySpark, pandas, or Dask.


* Proficiency in Python for data scienc...