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Oliver Wyman - Sr. Lead Data Scientist or Principal Data ScientistOliver Wyman • Chicago, Illinois, United States
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Oliver Wyman - Sr. Lead Data Scientist or Principal Data Scientist

Oliver Wyman
  • US
    Chicago, Illinois, United States
  • US
    Chicago, Illinois, United States
Jetzt Bewerben

Über

Boston, Chicago, New York, Dallas, Toronto, Montreal Lead Data Scientist Oliver Wyman Digital is a leading practice that partners with clients to deliver breakthrough outcomes for their toughest digital challenges. By blending deep industry expertise with digital technology, we aim to accelerate and embed digital transformation, modernize technology, and harness value from data and analytics. The Role And Responsibilities As a Lead Data Scientist, you are primarily responsible for managing technical projects, including data engineering, model selection and design, and infrastructure deployment in both internal and client environments. You will work with varied teams, engage directly with clients, and collaborate with OW Digital specialists and consultants.
Exploring data, building models, and evaluating solution performance to resolve core business problems Explaining, refining, and collaborating with stakeholders through the journey of model building Keeping up with your domain’s state of the art & developing familiarity with emerging modelling and data engineering methodologies Advocating application of best practices in modelling, code hygiene and data engineering Leading the development of proprietary statistical techniques, algorithms or analytical tools on projects and asset development Working with Partners and Principals to shape proposals that leverage our data science and engineering capabilities
Your Experience & Qualifications
Technical background in computer science, data science, machine learning, artificial intelligence, statistics, or other quantitative and computational science Compelling track record of designing and deploying large-scale technical solutions, which deliver tangible, ongoing value including:
Building and deploying robust, complex production systems that implement modern data science methods at scale, including supervised learning (regression and classification with linear and non‑linear methods) and unsupervised learning (clustering, matrix factorization methods, outlier detection, etc.) Leveraging cloud‑based infrastructure‑as‑code (CloudFormation, Bicep, Terraform, etc.) to minimize deployment toil and enabling solutions to be deployed across environments quickly and repeatably Demonstrating comfort and poise in environments where large projects are time‑boxed, and therefore consequential design decisions may need to be made and acted upon rapidly
Demonstrated fluency in modern programming languages for data science (i.e. at least Python, other expertise welcome), covering the full ML lifecycle (e.g. data storage, feature engineering, model persistence, model inference, and observability) using open‑source libraries, including:
Knowledge of one or more machine learning frameworks, including but not limited to: Scikit‑Learn, TensorFlow, PyTorch, MxNet, ONNX, etc. Familiarity with the architecture, performance characteristics and limitations of modern storage and computational frameworks, with cloud‑first considerations for Azure and AWS particularly welcome 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:
Deep understanding of a class of modelling or analytical techniques (e.g. Bayesian modeling, time‑series forecasting, etc.) Fluency in the mathematical principles and generalizations of data science – e.g., Statistics, Linear Algebra and Vector Calculus
Experience presenting at high‑impact data science conferences and solid connections 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, Healthcare and Life Sciences, Consumer, Retail, Energy, or Transportation industries
YOUR ATTRIBUTES
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 for targeted client and/or internal stakeholder meetings
OUR VALUES & CULTURE
Rewarding work – High quality projects with major brands and recognition. Progressive employment – Flat structures, I&D values, merit‑based progression, healthcare options, 401k matching, and continuous improvement. Enjoyable days – Mentoring, development, sponsorship, and community work opportunities. Balanced lives – Flexible hours, work‑from‑home options, and hybrid office model with required onsite days.
Compensation & Benefits Base salary range: $150,000 to $195,000. Eligibility for performance‑based incentives.
Health and welfare benefits, tuition assistance, 401K savings and other retirement programs Employee assistance programs Flexible hours and ability to work from home Hybrid work model with office presence required at least three days per week, with anchor day schedule
Oliver Wyman is an equal opportunity employer. #J-18808-Ljbffr
  • Chicago, Illinois, United States

Sprachkenntnisse

  • English
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