Your responsibilities will include
- Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges
- Exploring large-scale data and crafting models to answer core business problems
- Working with partners and principals to shape proposals that showcase our data science and analytics capabilities
- Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building
- Advocating best practices in modelling and code hygiene
- Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects
- Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them
- Keeping up with emerging state-of-the-art modelling and data science techniques in your domain
Your Attributes, Experience & Qualifications
- Bachelors or Master s degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering)
- Prior experience in data science, machine learning, and analytics
- Passion for problem-solving through big-data and analytics
- Pragmatic and methodical approach to solutions and delivery with a focus on impact
- Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment
- Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications
- Excellent verbal and written communication skills and complete command of English
- Willingness to travel
- Collaborative team player
- Respect for confidentiality
Technical Background
- Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet)
- Prior experience in designing and deploying large-scale technical solutions leveraging analytics
- Solid foundational knowledge of the mathematical and statistical principles of data science
- Familiarity with cloud storage, handling big data, and computational frameworks
- Valued but not required:
- Compelling side projects or contributions to the Open-Source community
- Experience presenting at data science conferences and connections within the data science community
