Data Scientist

Marsh (nyse: Mrsh)
Rotterdam, Netherlands
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
Italian, Dutch, English, Spanish, French, German

Job location

Remote
Rotterdam, Netherlands

Tech stack

Data Mining
Python
Machine Learning
NumPy
TensorFlow
SQL Databases
Unstructured Data
PyTorch
Vba Programming Language
Programming Languages

Job description

  • Develops modeling approaches for implementing new, market-leading analytics-based tools to understand and address risk
  • Understands business problems to create an approach that starts with determining structured and unstructured data needs and availability, builds Machine Learning models, and finalizes with results that unlock insight for clients and colleagues
  • Demonstrates skill in advanced statistical analysis, data mining, and/or research techniques, combined with broader awareness of the business and ongoing research, while functioning in a collaborative role with the Data Science team and across the wider organization
  • Stays current with ongoing research in the field and brings new approaches to the team
  • Serves as an internal expert resource and champion for data science and/or actuarial science within Marsh and MMC
  • Coaches team members on the delivery of analytics-based tools and analyses and presentation of findings

Requirements

  • Master's Degree in Math, Statistics, Data Science, Actuarial Science or related field
  • Expert statistical modeling knowledge, including familiarity with machine learning techniques
  • Ability to face difficult and sometimes complex problems
  • Ability to influence others within and outside of the job function regarding approach and procedures
  • Ability to develop strong internal/external client oriented solutions
  • Superior detail orientation, excellent communication and interpersonal skills
  • Knowledge of modern programming languages such as Python, including NumPy, TensorFlow, SQL, and PyTorch
  • R or VBA may be helpful but not required

Language: English required and another European language such as Dutch, French, German, Italian or Spanish.

Benefits & conditions

a competitive salary package Uren Full time Contractvorm Vast dienstverband Locatie Rotterdam Niveau Medior Sector Verzekeringen en Pensioenen Deel deze vacature: E-mailen

This position is for an individual contributor in Data Science and/or actuarial science, who will develop and implement models using leading-edge techniques in machine learning, predictive modeling, artificial intelligence, and natural language processing as applied in commercial insurance and risk management. This position consults with clients and colleagues on complex actuarial, financial and statistical analyses, and develops approaches for new, market-leading analytics-based tools.

About the company

Marsh Risk is a business of Marsh (NYSE: MRSH), a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information about Marsh Risk, visit marsh.com, or follow us on LinkedIn and X. Marsh is committed to creating a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one "anchor day" per week on which their full team will be together in person.

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