Job Description

The Role and Responsibilities We are looking to hire an Associate Director in Data Science & Data Engineering Track. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. In the data engineering track, you will be primarily responsible for developing and monitoring high-performance applications that can rapidly deploy latest machine learning frameworks and other advanced analytical techniques at scale. This role requires you to be a proactive learner and quickly pick up new technologies, whenever required. Most of the projects require handling big data, so you will be required to work on related technologies extensively. You will work closely with other team members to support project delivery and ensure client satisfaction. 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 Bachelor's or Masters 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 (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 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 Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence Technical Background (Data Engineering) Prior experience in designing and deploying large-scale technical solutions Fluency 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, Glue Strong SQL skills and experience with relational databases such as MySQL, PostgreSQL, or Oracle Experience with big data tools like Hadoop, Spark, Kafka Demonstrated knowledge of data structures and algorithms Familiarity with version control systems like GitHub or Bitbucket Familiarity with modern storage and computational frameworks Basic understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security Valued but not required: Compelling side projects or contributions to the Open-Source community Prior experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Familiarity with containerization technologies, such as Docker and Kubernetes Experience with UI development using frameworks such as Angular, VUE, or React Experience with NoSQL databases such as MongoDB or Cassandra Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence