Machine Learning Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

American International Group, Inc. (AIG) is a leading global insurance organization. Building on 100 years of experience, today AIG member companies provide a wide range of property casualty insurance, life insurance, retirement solutions, and other financial services to customers in more than 80 countries and jurisdictions. These diverse offerings include products and services that help businesses and individuals protect their assets, manage risks and provide for retirement security.

Get to know the business

Our team is developing an AI-first product to support AIG’s Investments department make commercial real estate investment decisions. This is mainly achieved through the incubation of disruptive innovation via scientists, engineers and designers working together. The resulting solution optimize the investment process by embracing innovation and integrating advanced methods and technologies currently disrupting our industry, such as AI, digital transformation and alternative data, to improve investment decision making, performance, and risk management.

As a critical role in our success, we are looking to hire a 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 Machine Learning Scientist; along the way this role will contribute to find new signals and sources of alpha, enable decision makers digest large amount of structured and unstructured information in a smart (fast, efficient, and accurate) way, and flag risks earlier than conventional methods.

About the role

What you need to know:

•  Employ the existing (and develop new) machine learning algorithms that can find (predictive) patterns in large financial data sets.
• 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).

What we’re looking for:

• An advanced degree (e.g., PhD) in a numeric discipline (e.g., Statistics, Machine Learning, Computer Science or 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 statistical theories, methodologies, and inference tools (e.g., hypothesis testing, (generalized) linear models, additive models, mixed-effect models).
• Proven track record in some of the advanced topics such as Bayesian inference, hierarchical models, deep learning, and Gaussian processes. 
• 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.
• 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

• 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.
• Employing machine learning in collaborative commercial settings (e.g., using DevOps methodologies and tools such as GitHub), ideally, in collaboration with product development teams. 
• Experience in 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.