Description

parkCognition catalyzes sustainable growth for their clients throughout the world with proven artificial intelligence (AI) systems, award-winning machine learning technology, and a multinational team of AI thought-leaders. Clients are trusted with advancing lives, infrastructure, sustainability, and financial systems across the globe. They partner with SparkCognition to understand their industry’s most pressing challenges, analyze complex data, empower decision-making, and transform human and industrial productivity. With leading-edge artificial intelligence products—Darwin®️, DeepArmor®️, SparkPredict®️, and DeepNLP^TM—SparkCognition’s clients can adapt to a rapidly changing digital landscape and accelerate their business strategies. 

This position is within AIM2, a subsidiary of SparkCognition. AIM2 is a fast-growing fintech applying artificial intelligence and machine learning to fixed-income market-making. The firm currently has employees in New York, London, and Austin, TX.

This position requires a background in deep learning, reinforcement learning, and generative processes or similar. The desired candidate should have a quantitative background, experience working with time series, and strong coding skills. Prior experience in the finance industry is good but not a requisite.

Responsibilities

The candidate will help drive and enhance AIM2’s data-driven investment initiatives, improve upon the existing deep reinforcement algorithm, provide innovative ways to upgrade the process, and generate alternative solutions. The role is central and is built around collaboration with quants who have extensive domain knowledge, various technology teams in AIM2 and SparkCognition, and business units that collate feedback from our clients. The company is highly data-driven, and analyses are peer-reviewed with a strong culture of collaboration and openness.

Requirements

• Strong understanding of Data Science, including machine learning, statistics, probability, and modeling.
• Significant experience with Data Science programming languages, such as Python, R, Matlab
• Significant experience with machine learning frameworks, such as PyTorch, TensorFlow, Theano, and Keras. 
• Applied knowledge of ML techniques/algorithms including linear models, neural networks, decision trees, Bayesian techniques, clustering, reinforcement learning, and anomaly detection
• Ability to form strong working relationships with team members
• Degree in Computer Science, Statistics, Physics, Mathematics, Engineering, or a related scientific discipline

Preferred Qualifications

• Graduate degree (or 5-8 years of equivalent experience) in one of the fields above
• Prior  experience in Quantitative Finance (buy or sell-side)