Deloitte & Touche LLP seeks a Master Data Scientist in McLean, VA.
Work You’ll Do
Responsible for leading and directing a team focused on developing cutting-edge quantitative solutions to our clients' most challenging problems. Drive the application of rigorous data science within Deloitte's Artificial Intelligence ("Al") Center of Excellence ("CoE") and across Deloitte. Lead improvements in methodology or initiatives to address capability gaps or increase efficiency. Influence machine learning strategy for clients/programs/projects. Explore design options to assess efficiency and impact, develop approaches to improve robustness and rigor. Lead discussions at peer review and use quantitative skills to positively influence decision making. Effectively explain technical concepts at all levels in the organization, including senior leaders/stakeholders. Identify opportunities to apply the latest advancements in Machine Learning and Artificial Intelligence to build, test, and validate predictive models. Deploy algorithms to production to identify actionable insights from large databases. Make impactful contributions to internal discussions on emerging machine learning methodologies.
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Requirements
- PhD degree in Mathematics, Neuroscience, Engineering or related field (willing to accept foreign education equivalent).
- One year of experience designing, implementing, and delivering Artificial Intelligence/ Machine Learning (AI/ML) models.
- Experience must include one year of:
- Creating algorithms to extract information from large, multiparametric data sets;
- Developing and embedding automated processes for predictive model validation, deployment, and implementation;
- Developing and implementing AI/ML models to support both internal and external projects;
- Working with external stakeholders to identify issues, and designing AI/ML solutions to address those issues;
- Leading teams of data scientists to code and develop production-level solutions;
- Coding AI/ML solutions using Python, including deep learning frameworks and libraries;
- Working on cloud platforms, including AWS, GCP, and Azure, to develop and test ML models;
- Leading implementation strategies of ML modules into existing solutions;
- Coordinating with both technical and non-technical partners within the client and internally; and
- Maintaining code quality guidelines, performing research to ensure solutions are consistent with leading technologies, and mentoring junior team members in strategies, guidelines and methodologies in AI/ML.