Science team at AIG develops AI-first products and services (apps and solutions that use machine learning to inform and assist their users) for the Investment arms of AIG. This is mainly achieved through:
Incubation of disruptive innovation (via scientists, engineers and designers working together) Machine learning R&D (and publication in top AI/ML conferences and journals) Provision of machine-learning advisory / consulting to AIG's global businesses.
The resulting solutions aim to optimize the Investments process by embracing innovation and integrating advanced methods and technologies currently disrupting our industry, such as AI, digital transformation and alternative data, in order to improve investment decision making, performance, and risk management.
As a critical role in Sciences success, we are looking to hire Statistical Machine Learning Scientists to join our team and contribute to the development and implementation of the algorithmic core of a series of innovative products / projects.
This is an exciting opportunity for those who want to enjoy state-of-the-art R&D and be challenged and grow as a Statistical Machine Learning Scientist; along the way this role will contribute to find new signals and...
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This is an exciting opportunity for those who want to enjoy state-of-the-art R&D and be challenged and grow as a Statistical Machine Learning Scientist; along the way this role will contribute to find new signals and sources of alpha, enable analysts/PM to digest large amount of structured/unstructured information in a smart (fast, efficient, and accurate) way, flag risks earlier than conventional methods in the Big Data world.
Responsibilities and Performance Objectives
Employ the existing (and develop new) Machine Learning algorithms that can find (predictive) patterns in large multi-modal data.
Provide innovative solutions for investment problems (e.g., by translating complex commercial problems to Machine Learning problems).
Be an active member of teams that provide the business with AI-first apps, and data-driven insights and strategies.
Participate in, lead, and create cross-functional projects and training.
Communicate (both oral and written) with colleagues and stakeholders (both internal and external).
For more senior candidates: lead, inspire and mentor junior scientists and research assistants (interns).
Both senior candidates (e.g., with years of relevant post-doctoral and/or industrial experience) and junior candidates are welcome to apply; we have and will offer positions appropriate to expertise and level of experience.
The minimum required skills include:
An advanced degree (e.g., PhD) in a numeric discipline (e.g., Statistics, Machine Learning, Computer Science, and Signal Processing).
Scientific expertise and applied experience in Machine Learning (ideally, a combination of excellent academic research and high-impact commercial projects).
In depth understanding of common Machine Learning algorithms (e.g., for classification, regression and clustering).
In depth knowledge of advanced statistical theories, methodologies, and inference tools (e.g., hypothesis testing, (generalized) linear models, additive models, mixture models, non-parametric models).
Proven track record in some of the advanced topics such as Bayesian inference, hierarchical models, deep learning, Gaussian processes, and causal inference.
Advanced programming skills in Python and/or R (and their related data processing, Machine Learning, and visualization libraries).
Practical experience in preparing data for Machine Learning (e.g., using SQL and/or NoSQL technologies).
Completion of at least one significant project (equivalent of a great PhD research project, and/or a high-impact commercial project) in applied Machine Learning.
Excellent (written and oral) communication skills.
An ideal candidate (is not required to, but) will also have
Integration of Machine Learning algorithms with big-data platforms (e.g., Spark) and high-performance computing ecosystems (e.g., CUDA).
Familiar with AWS eco-system in terms of model training, distribution, and production.
Programming in C++ and/or Java.
Deployment of algorithms as real time / highly available services.
Integration with front-end systems (e.g., HTML5/ native mobile apps).
Employing Machine Learning in collaborative commercial settings (e.g., using DevOps methodologies and tools such as GitHub), ideally, in collaboration with product development teams.
Leading scientific projects.
Publication record in (and willingness to represent AIG in) top statistic (e.g., JRSS, JASA, Bka, AoS, JRSB, Bcs, and JCGS) and/or machine learning (e.g., AI, TPAMI, IJCV, and JMLR) journals and conferences (e.g., NIPS, ICML, AAAI, CVPR, IJCAI, ACL, EMNLP, and AISTATS).
Experience of working with engineering and design / product teams.
Senior candidates should have proven ability to engage with business, formulate technical problems from business needs and craft solutions to shape business priorities.
It has been and will continue to be the policy of American International Group, Inc., its subsidiaries and affiliates to be an Equal Opportunity Employer. We provide equal opportunity to all qualified individuals regardless of race, color, religion, age, gender, gender expression, national origin, veteran status, disability or any other legally protected categories.
At AIG, we believe that diversity and inclusion are critical to our future and our mission " creating a foundation for a creative workplace that leads to innovation, growth, and profitability. Through a wide variety of programs and initiatives, we invest in each employee, seeking to ensure that our people are not only respected as individuals, but also truly valued for their unique perspectives.