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 analyticsPassion for problem-solving through big-data and analyticsPragmatic and methodical approach to solutions and delivery with a focus on impactIndependent worker with the ability to manage workload and meet deadlines in a fast-paced environmentImpactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implicationsExcellent verbal and written communication skills and complete command of EnglishWillingness to travelCollaborative team playerRespect for confidentialityTechnical Background (Data Science)
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 analyticsSolid foundational knowledge of the mathematical and statistical principles of data scienceFamiliarity with cloud storage, handling big data, and computational frameworksValued but not required :Compelling side projects or contributions to the Open-Source communityExperience presenting at data science conferences and connections within the data science communityInterest / background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presenceTechnical Background (Data Engineering)
Prior experience in designing and deploying large-scale technical solutionsFluency in modern programming languages (Python is mandatory; R, SAS desired)Experience with AWS / Azure / Google Cloud, including familiarity with services such as S3, EC2, Lambda, GlueStrong SQL skills and experience with relational databases such as MySQL, PostgreSQL, or OracleExperience with big data tools like Hadoop, Spark, KafkaDemonstrated knowledge of data structures and algorithmsFamiliarity with version control systems like GitHub or BitbucketFamiliarity with modern storage and computational frameworksBasic understanding of agile methodologies such as CI / CD, Applicant Resiliency, and SecurityValued but not required :
Compelling side projects or contributions to the Open-Source communityPrior experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras / Theano, Torch, Caffe, MxNet)Familiarity with containerization technologies, such as Docker and KubernetesExperience with UI development using frameworks such as Angular, VUE, or ReactExperience with NoSQL databases such as MongoDB or CassandraExperience presenting at data science conferences and connections within the data science communitySkills Required
Tensorflow