Senior Data Scientist – Predictive Analytics (Contract Role)
We are seeking a highly skilled Senior Data Scientist to join a predictive analytics initiative focused on client credit scoring and financial risk modeling. The team has already defined requirements, designed the tools, and prepared the data—this role is about execution and effective delivery rather than building from scratch. You will collaborate with junior data scientists and partner with experienced senior data scientists elsewhere in the organization, ensuring models are developed, validated, and deployed efficiently.
This is an ideal opportunity for a strong operator who can quickly plug in and drive results in a fast-paced environment.
Key Responsibilities
- Develop and deploy predictive models for credit scoring and financial risk assessment.
- Collaborate with junior data scientists and business stakeholders to ensure alignment on objectives and deliverables.
- Clean, transform, and configure datasets for modeling and production use.
- Build, validate, and optimize ML models, ensuring high accuracy and reliability.
- Work hands-on with Python, Jupyter Notebooks, and AI/ML frameworks to deliver actionable insights.
- Deploy and manage ML models on AWS cloud environments.
- Document methodologies, workflows, and results for both technical and non-technical audiences.
Required Qualifications
- Proven experience in predictive analytics, preferably in financial services, credit scoring, or risk modeling domains.
- Strong expertise in Python, AI/ML libraries (e.g., scikit-learn, TensorFlow, PyTorch), and Jupyter Notebooks.
- Solid understanding of data preparation, transformation, and configuration for modeling.
- Hands-on experience deploying ML models in AWS environments (e.g., S3, SageMaker, Lambda).
- Strong communicator with the ability to explain technical details clearly to non-technical stakeholders.
- Fluent in English and able to work collaboratively in a distributed team.
- Proactive, self-directed operator who can execute with minimal ramp-up.
Nice-to-Haves
- Experience mentoring or guiding junior data scientists.
- Familiarity with cloud-based ML workflows beyond AWS (e.g., Azure, GCP).
- Strong understanding of model validation, testing, and monitoring in production environments.
Logistics
- 100% remote; must work Pacific Time hours (Mexico City time acceptable).
- Contract role, 3–4 months with potential for extension.
- 1 & Done interview process – technical and functional combined.
- Immediate start preferred