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. You ll 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
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 (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