Oliver Wyman Digital Principal Data Scientist

Key Skills

Java Programming, Python Programming, SQL, Apache Kafka, Machine learning techniques, Data science techniques, Keras software library, PyTorch, TensorFlow, Apache Hive, Theano, Scikit-learn, HDFS, MxNet, SPARK Programming, Caffe, VR/AR frameworks

Job Description

ojects are the same. You’ll be working with varied and diverse teams to deliver unique and unprecedented products across industries. The Principal Data Scientist is primarily responsible for advancing Oliver Wyman’s broad capabilities to use and deploy cutting edge data scientific tools and methods in our projects, platforms and products. S/he both anchors our current best practices by designing and building reusable data science assets, and simultaneously works to keep OW on the bleeding edge by understanding the very latest and most sophisticated methods and tools for grappling with extremely large scale and complex problems. As a Data Scientist, you will work alongside Oliver Wyman partners in the Digital and other practice groups, engage directly with clients to understand their business challenges, and craft appropriate solutions to be delivered by OW Digital specialists and consultants.

Your responsibilities will include, for example:

• Exploring data and crafting models to answer core business problems that may not have a common blueprint
• Guiding data science consultants on the best path to solving problems in a specific technical domain in which you are the expert
• Explaining, refining, and crafting model insights and architecture to bring stakeholders through the journey of model building
• Inventing and pioneer R&D efforts to bring new approaches and state of the art methods to our clients
• Codifying best practice approaches to specific analytical problems in the form of accessible, reusable patterns, templates, and code bases
• Leading efforts to standardize and industrialize solutions such that they can be robustly deployed into production and/or scaled up far beyond the laptop-scale

YOUR EXPERIENCE & QUALIFICATIONS

You are a well-rounded technologist who brings a wealth of real-world experience and a:

• Technical background in computer science, data science, machine learning, artificial intelligence, statistics or other quantitative and computational science
• A compelling track record of designing and deploying large scale technical solutions, which deliver tangible, ongoing value:
• Direct experience having built and deployed complex production systems that implement modern, data scientific methods at scale and do so robustly
• Comfort in environments where large projects are time-boxed and therefore consequential design decisions may need to be made and acted upon rapidly
• Fluency with cluster computing environments and their associated technologies, and a deep understanding of how to balance computational considerations with theoretical properties of potential solutions
• Ability to context-switch, to provide support to dispersed teams which may need an “expert hacker” to unblock an especially challenging technical obstacle
• Demonstrated fluency in modern programming languages for data science, covering a wide gamut from data storage and engineering frameworks through machine learning libraries
• Expert knowledge of at least one and probably several core machine learning frameworks, including but not limited to: TensorFlow, Keras/Theano, Torch, Caffe, MxNet; Scikit-Learn, etc.
• Deep understanding of the architecture, performance characteristics and limitations of modern storage and computational frameworks, with experience implementing solutions that leverage: HDFS/Hive; Spark/MLlib; Kafka, etc.
• A history of compelling side projects or contributions to the Open-Source community is valued but not required
• Solid theoretical grounding in the mathematical core of the major ideas in data science
• Expert level understanding of a class of modelling or analytical techniques, often supported by Masters- or Doctoral-level research in the subject
• Deep fluency in the mathematical ‘primitives’ and generalizations of data science – e.g., expertise in Linear Algebra, and Vector Calculus
• Experience presenting at high-impact data science conferences and solid linkages to the data science community (e.g., via meetups, continuing relationships with academics, etc.) is highly valued
• Interest/background in Financial Services, and capital markets in particular; Health and Life Sciences; Consumer, Retail, Energy, or Transportation

YOUR ATTRIBUTES

Our team comprises all sorts of people from all sorts of backgrounds. We don’t care whether you’re loud or quiet, funny or serious, introverted or extroverted. We do, however, ask that you have:

• An undergraduate or advanced degree from a top academic program
• A genuine passion for technology and solving problems
• A pragmatic approach to solutioning and delivery
• Excellent communication skills, both verbal and written
• A clear commitment to creating impactful solutions that solve our clients’ problems
• The ability to work fluidly and respectfully with our incredibly talented team
• Willingness to travel (when it's safe to do so)

OUR VALUES & CULTURE

• We’re serious about making OW Digital a rewarding, enjoyable, and balanced place to work.

Rewarding work

• We’ve worked hard to earn our reputation for high quality work. That reputation allows us to work with major brands at all levels on incredibly exciting projects. Combine that with Oliver Wyman’s status as one of the Fortune 100 “Best Companies to Work For”, and you get a rewarding combination of challenge, support and recognition.

Progressive employment

• Flat organizational structures, resolute I&D values and a commitment to rewarding good work make for a progression path truly based on merit. A menu of healthcare options, 401k matching, and a culture of continuous improvement means your work gets more rewarding over time.

Enjoyable days

• We want our team members to build a career here—and to be happy. That makes us serious about caring for, mentoring, developing and sponsoring each other.
• This commitment also leads to opportunities for social impact and community work on company