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Product Manager - Data Science

Company: Marsh McLennan
Location: Hoboken
Posted on: May 7, 2022

Job Description:

The Senior Data Science Product Manager role within the Data Strategy group at Guy Carpenter ("GC") provides an opportunity to build and advance the data science program across multiple projects powering the business. You will own the business strategy, design, and coordination of varied data science solutions from data visualizations to pricing models to unique use cases for ML such as data prep and augmentation. You will be responsible for scoping analyses and strategizing novel products that monetize data. The Data Strategy group has a "start-up style" mandate and internal consulting role (within a $1.3 billion company) to effectively enhance the acquisition, storage, analysis, fidelity, and monetization of massive amounts of client, internal, and third-party data across the GC organization. Responsibilities

  • Work with business users, stakeholders and clients to understand business domain requirements and reflect them in the data science strategy
  • Determine the optimal balance between analysis, research, and productization
  • Learn about the business from stakeholders, and gain an intimate understanding of risk, insurance, and applications for data science and machine learning
  • Develop, implement, and deploy data science prototype products, to test product-market fit, and decide if worth industrializing further
  • Innovate new ways to leverage enormous amounts of various datasets to drive revenues via the development of new products with the Data Strategy team, as well as the enhanced delivery of existing products
  • Strategize how best to enable data science, and work with engineering and product managers to get important dependencies on the roadmap
  • Own the role of data steward for a variety of high value datasets and implement innovative quality assurance practices
  • Support strong data science research standards across the team through code reviews, KPI design, business explainability, and monitoring
  • Perform data analysis within Jupyter Notebooks to present analyses and concepts on new ideas, potential projects to the team and stakeholders
  • Evangelize data strategy techniques and best practices throughout global strategic advisory
  • Keep up to date on the latest trends and innovation in data technology and how these trends apply to GCs business and data strategy Required Qualifications
    • Desire and willingness to deeply learn re-insurance and actuarial sciences domain
    • Strong quantitative skills, including Bayesian statistics and probability theory
    • 5+ years of relevant experience as a product manager on data science related products
    • Strong experience with the full data science lifecycle and ML modeling frameworks
    • Strong understanding of modern data trends & principles (Machine Learning, AI, Natural Language, Crowdsourcing, Unstructured Data, Data Mining, Visualization) and the accompanying technology tooling ecosystem & vendor landscape
    • Experience and enthusiasm working with data in a variety of manners spanning proficiencies in Excel, SQL, API requests and basic scripting in Python or R
    • Familiarity with agile development principles; comfort collaborating & partnering with Data Engineers, Data Scientists, Data Business Analysts
    • Composure presenting in front of executives and other key stakeholders; understanding of different learning approaches and ability to tailor teaching strategies to different audiences
    • Possession of leadership skills, client-facing experience and the ability to influence internal & external stakeholders
    • Experience with documentation management and maintenance Preferred Qualifications
      • Experience with NLP techniques, deep learning, and more basic statistical inference (GLMs, kernel methods, etc.)
      • Experience building data science products in the risk/insurance/actuarial field, or demonstrated general domain knowledge through projects
      • Strong understanding of entity resolution, ML use in data prep, streaming technologies
      • Experience with web scraping and crowd sourcing technologies, as a useful toolkit to enable data science
      • Strong experience with modern data productivity frameworks and their alternatives such as Databricks, DataRobot, Alteryx
      • Experience with the MS Azure cloud environment

Keywords: Marsh McLennan, Hoboken , Product Manager - Data Science, Executive , Hoboken, New Jersey

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