Senior Manager - Data Science

We are seeking a talented individual to join our Data Science (Global Energy Practice) team at Marsh Risk. This role will be based in Mumbai. This is a hybrid role that has a requirement of working at least three days a week in the office.Senior Manager - Data Science This position is for an individual contributor in Data Science (Global Energy Practice), who will develop and implement leading-edge techniques in artificial intelligence, machine learning, predictive modeling, and natural language processing as applied in commercial insurance and risk management. This position consults with senior colleagues on complex NATCAT, financial and statistical analyses, and develops approaches for new, market-leading tools.We will count on you to:Hands on expertise in Python and data related packages such as pandas, numpy, matplotlib, streamlit etc.Hands on data visualization tools such as Power BI, Qliksense, Tableau.Experience with loss/exposure modeling, frequency – severity modelingDeep understanding of natural catastrophe phenomena such as earthquake, floods, wildfire etcMine and analyze data to drive optimization and implement business strategiesBuild machine learning algorithms based on the business askDeploy API on the platform by understanding the technical askDevelop statistical custom data models and algorithms from scratch to enhance current value proposition and new product developmentUtilize risk models related to Time Series Forecasting, Clustering, GLM/Regression, Boosting, Trees, etc.Use advanced analytics to augment consulting deliverables with data backed outputsConduct research on the clients’ risk areas and prepare a point of view for consulting.What you need to have: Phd/Masters in field related to natural catastrophe, risk analytics, actuarial science or any deep risk related firldsBachelors degree in Engineering, Computer Science, Data Science, or related fields8+ years of hands on experience in the field of Data Science, AI research or similar fieldsAbility to develop strong internal/external client-oriented solutionsSuperior detail orientation, excellent communication and interpersonal skillsHands-on expertise of modern programming languages such as Python and SQLHands-on expertise on Visualization tools as Power BI, Qliksense and Tableau.Expertise in writing complex SQL queries.Experience in writing front end Javascript code is a plus.What makes you stand out?Understanding of NATCAT phenomena, insurance and risk managementExperience of building data visualization in MS-excel, Power BIWhy join our team:We help you be your best through professional development opportunities, interesting work and supportive leaders.We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact on colleagues, clients and communities.Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $24 billion and more than 90,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit , or follow us on LinkedIn and X.Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, 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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