Data Scientist I

Join the Arium team at Verisk s Hyderabad, India office within Extreme Event Solutions. As a data scientist, you will contribute to the building of emerging and systemic liability catastrophe models and products designed to address risk estimation in our ever-evolving world. These catastrophe models rely on quantitative modeling and simulations of litigation outcomes. To produce unbiased risk estimates, our models carefully consider historical data changes, supplemented by subject matter expertise, where statistical uncertainty exists. Our products provide opportunities for creative problem-solving, data science, machine learning, and effective communication at the intersection of systemic liability risk, (re)insurance, and society. By doing so, we are making a tangible impact in the cutting-edge field of catastrophe risk modeling.

3+ years of hands-on experience in data science and machine learning
Extensive experience in statistical and probabilistic modeling
Proven ability in effective problem-solving and out-of-box thinking.
Demonstrated experience in model development from ground-up
Strong programming skills in Python, R, SQL.
Experience in cloud computing, and cloud-based services, i.e., AWS is added advantage
Ability to identify and process raw data, trends, analysis, and assessments in order to aggregate disparate information, leveraging both analytic and visualization tools.
Experience building production data solutions in (re)insurance.

Requirements:
BE/ B.Tech/M.Tech/M.Sc. degree from computer science, applied sciences (mathematics, physics, statistics), engineering, and/or finance.

Gather relevant data from various sources, i.e., historical data, financial data, and legal documents
Develop appropriate statistical and machine learning models (e.g., neural networks and deep learning, among others)
Develop prototype models to conduct various test and validation exercises.
Validate model results against real-world events and historical claims data.
Conduct sensitivity analyses to assess the robustness of the model under different assumptions.
Work closely with subject matter experts (e.g., actuaries, underwriters, academics, among others) to incorporate domain knowledge into models.
Understand legal, regulatory, and industry-specific requirements related to emerging and systemic catastrophe risk.
Explain complex technical concepts in a clear and concise manner.
Collaborate with cross-functional teams including actuarial, research, and software to ensure effective and efficient model builds.
Stay updated on advancements in data science, machine learning, and catastrophe modeling.
Explore new methodologies and techniques to enhance model accuracy and efficiency.
Contribute to data analysis, physical interpretation, and documentation.
Perform literature review and synthesis related to emerging and systemic liability risks and impacts of evolving world environments on various industry sectors.
Help interpret unfolding catastrophic events in the context of legal system and insurance impacts.
Help formulate answers to client questions related to the models and their output.