The partner company is looking to transform how organizations manage financial risk and optimize spend by designing, building, and enhancing AI-powered analytics solutions.
Requirements
- Strong experience in applied machine learning with large datasets and advanced statistical methods.
- Proficiency in Python and SQL for data analysis, modeling, and pipeline development.
- Knowledge of regression, decision trees, random forests, SVMs, clustering, and ensemble methods.
- Experience analyzing structured and unstructured data, with expertise in predictive modeling, optimization, and causal inference.
- Hands-on experience with Linux environments and both R&D and production software development.
Responsibilities
- Lead the development of machine learning projects from requirements gathering to deployment, collaborating with stakeholders throughout the process.
- Design, implement, and maintain ML pipelines, including data ingestion, feature engineering, modeling, evaluation, and deployment.
- Conduct research and develop advanced analytical and optimization methods to enhance platform capabilities.
- Identify opportunities to apply AI and statistical techniques to solve complex business problems.
- Mentor and provide guidance to team members, fostering knowledge sharing and technical growth.
- Ensure model performance and robustness by diagnosing overfitting and other issues, and iteratively improving solutions.
Other
- Bachelor’s degree in Computer Science with emphasis in Data Science, plus at least 5 years of relevant experience.
- Minimum of 3 years of professional experience using Python in data science projects.
- Strong communication skills and ability to collaborate across cross-functional teams.
