4 Probability Concepts Jobs

You will be responsible for applying Insurance & Re-insurance policy conditions, analyzing client exposure data against different perils, and quantifying natural catastrophe risk based on catastrophe modeling software. It is essential to maintain clients" Turn Around Time and quality consistently. You should possess the ability to understand and interpret losses and prepare various reports according to client requirements. With a minimum of 2 years of experience in the catastrophe modeling industry, you should have hands-on experience with Verisk's Touchstone / TS Re software. Understanding and interpreting CAT Modeling losses, as well as knowledge of policy structure (layers, limits, deductibles) within the (re)insurance industry, are crucial. Attention to detail, superior communication skills, strong analytical and quantitative skills, along with a solid understanding of probability concepts are necessary. Proficiency in Microsoft Excel and SQL is required, and programming skills in SQL, R, Python are highly beneficial. A degree in Insurance, mathematics, actuarial science, or business is also a prerequisite. Verisk, a leading data analytics and technology partner to the global insurance industry for over 50 years, values expertise and scale to deliver value to clients. The company empowers communities and businesses to make better decisions on risk faster. Verisk offers a supportive and inclusive workplace culture that values learning, caring, and results while making inclusivity and diversity a top priority. Recognized as a Great Place to Work for workplace culture in multiple countries and by various publications, Verisk is committed to innovation and ethical pursuits. The company is looking for individuals who can help translate big data into big ideas to create an exceptional experience for themselves and contribute to a better tomorrow for future generations. Verisk's business units include Underwriting Solutions, Claims Solutions, Property Estimating Solutions, Extreme Event Solutions, Specialty Business Solutions, Marketing Solutions, Life Insurance Solutions, and Verisk Maplecroft, each offering unique data-driven solutions to support individuals, businesses, and society in becoming more resilient to various challenges. As an equal opportunity employer, Verisk Analytics values diversity and encourages individuals to join the team and contribute to the company's mission of translating data into valuable insights that drive positive change. For more information on career opportunities at Verisk, please visit their [careers page](https://www.verisk.com/company/careers/).,

As a Machine Learning Engineer, you will be responsible for designing and deploying machine learning solutions. Your role will require deep expertise in algorithms, proficiency in programming languages like Python, and familiarity with specialized frameworks. You will lead complex machine-learning projects, make critical architectural decisions, optimize models for performance, and collaborate with interdisciplinary teams. Additionally, you will contribute to cutting-edge research, develop innovative solutions, and stay updated with the latest advancements in the field to deliver impactful and state-of-the-art machine learning applications. Your key responsibilities will include designing and programming machine learning methods, integrating them into our ML framework/pipeline, evaluating and validating the analysis using statistical methods, and presenting the findings in a clear manner to individuals not well-versed in data science/computer science. You will also need to stay abreast of the latest trends in machine learning, deep learning, and related fields, as well as collaboratively design and implement machine learning systems and infrastructure to drive successful outcomes. To qualify for this role, you should ideally hold a B.E./B.Tech/M.E./M.S./M.Tech/PhD in fields related to Computer Science, coupled with experience in machine learning, image, and signal processing, or statistics. A background in recent advances in machine learning, deep learning, natural language processing, and/or image/signal/video processing, along with at least 2 years of professional work experience dealing with real-world data, will be advantageous. Strong programming skills and knowledge of software engineering concepts, familiarity with machine learning libraries like Tensorflow, Jax, Keras, Scikit-learn, and PyTorch, as well as excellent mathematical abilities including accuracy, significance tests, advanced probability concepts, and linear algebra are essential. Moreover, the ability to conduct independent and collaborative research and excellent written and verbal communication skills are also key requirements for this role.,

As a Machine Learning Engineer, you will utilize your expertise to contribute to the development of a world-leading capability in the domain of machine learning. Your responsibilities will involve participating in the design, development, deployment, testing, maintenance, and enhancement of machine learning software solutions. You will be tasked with applying machine learning, deep learning, and signal processing techniques to large datasets such as audio, sensors, images, videos, and text in order to develop models. Additionally, you will be responsible for architecting large-scale data analytics and modeling systems, designing and programming machine learning methods, and integrating them into the ML framework and pipeline. Collaboration with data scientists and analysts to support the development of ML data pipelines, platforms, and infrastructure will be a key aspect of your role. You will also evaluate and validate analysis using statistical methods and present findings in a clear manner to individuals not well-versed in the fields of data science and computer science. Furthermore, you will create microservices and APIs for serving ML models and services, evaluate new machine learning methods for adoption, and conduct feature engineering to enhance model performance. Your background should include knowledge of recent advances in machine learning, deep learning, natural language processing, and image/signal/video processing, with at least 5 years of professional experience in real-world applications. Strong programming skills in languages such as Python, Pytorch, MATLAB, C/C++, and Java, along with familiarity with software engineering concepts like OOP and design patterns, are essential. Proficiency in machine learning libraries such as TensorFlow, Keras, scikit-learn, and PyTorch is required. Additionally, you should possess excellent mathematical abilities, including expertise in accuracy, significance tests, visualization, and advanced probability concepts. Experience in architecting and implementing end-to-end solutions for accelerating experimentation and model building is highly desirable. A working knowledge of various machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and the ability to conduct independent and collaborative research are crucial for success in this role. Strong written and verbal communication skills are also important. Candidates with a B.E./B.Tech./B.S. degree and at least 3 years of experience in machine learning, deep learning, natural language processing, or image/signal processing will be considered. Preferably, candidates with an M.E./M.S./M.Tech./PhD in fields related to Computer Science and experience in machine learning, image and signal processing, or statistics are preferred for this position.,

As a Machine Learning Engineer, you will be applying your expertise to help develop a world-leading capability in the domain of machine learning. Your responsibilities will include contributing to the design, development, deployment, testing, maintenance, and enhancement of machine learning software solutions. You will work on applying machine learning, deep learning, and signal processing techniques on large datasets such as audio, sensors, images, videos, and text to develop models. Additionally, you will be involved in architecting large scale data analytics and modeling systems, designing and programming machine learning methods, and integrating them into the ML framework and pipeline. Collaboration with data scientists and analysts to support the development of ML data pipelines, platforms, and infrastructure will be a key aspect of your role. You will evaluate and validate analyses using statistical methods and present findings in a clear manner to individuals not familiar with data science or computer science. Furthermore, you will create microservices and APIs for serving ML models and services, evaluate new machine learning methods, and perform feature engineering to enhance model performance. The required skills for this role include a background and knowledge of recent advances in machine learning, deep learning, natural language processing, and image/signal/video processing, with around 5 years of professional work experience in real-world applications. Proficiency in programming languages such as Python, Pytorch, MATLAB, C/C++, and Java, along with knowledge of software engineering concepts like OOP and design patterns, is essential. Familiarity with machine learning libraries such as Tensorflow, Keras, scikit-learn, and pyTorch is also required. A strong mathematical background with skills in accuracy, significance tests, visualization, and advanced probability concepts is necessary. You should be capable of architecting and implementing end-to-end solutions for accelerating experimentation and model building, as well as possessing knowledge of various machine learning techniques such as clustering, decision tree learning, and artificial neural networks. The ability to conduct both independent and collaborative research, along with excellent written and spoken communication skills, is crucial. Preferred qualifications include a B.E./B.Tech/B.S. degree with 3+ years of experience in the relevant fields or an M.E./M.S./M.Tech/PhD, preferably in Computer Science, with experience in machine learning, image and signal processing, or statistics.,